CN103716622B - Image processing method and device - Google Patents

Abstract

A method for image processing, the method comprising: determining a first training filter according to a non-smooth region image block of an enhancement layer image and a non-smooth region image block of a base layer image, so that the first training filter satisfies : The similarity between the first prediction information determined according to the first training filter and the non-smooth region image block of the base layer image and the first original information determined according to the non-smooth region image block of the enhancement layer image satisfies the first A preset condition, wherein the base layer image corresponds to the enhancement layer image; according to the first training filter, an alternative upsampling filter is determined, wherein the candidate upsampling filter includes the first training filter; determine a target upsampling filter from the candidate upsampling filter; determine prediction information according to the target upsampling filter and the base layer image block; perform encoding processing on the target image block according to the prediction information, to generate the target code stream.

Description

Method and device for image processing

technical field

The present invention relates to the field of video processing, and more particularly, to an image processing method and device for image processing.

Background technique

With the rapid development of the Internet and the increasingly rich material and spiritual culture of people, there are more and more requirements for video applications on the Internet, especially for high-definition video applications, and the data volume of high-definition videos is very large. For transmission in the Internet with limited bandwidth, the problem that must be solved first is the problem of high-definition video compression and encoding.

In the network environment (such as the Internet), because the network bandwidth is limited, the needs of terminal equipment and users are different, so it is not satisfactory and effective to compress the code stream for a specific application. For some specific users or devices, it may not even make sense. An effective way to solve this problem is to use scalable video coding (SVC, scalable video coding) technology. In the SVC technology, an image is divided into multiple image layers according to quality parameters including spatial resolution, temporal resolution, or signal-to-noise ratio strength. The goal of SVC is to make the high-quality image layer make full use of the information of the low-quality image layer as much as possible, improve the efficiency of inter-layer prediction, and make the encoding of high-quality images more efficient.

When performing layered encoding on high-quality images, due to different resolutions, it is necessary to upsample low-quality images to achieve the same resolution as high-quality images, and then use the information of low-quality images to update the enhancement layer. Make predictions. Therefore, the effect of upsampling will have a direct impact on the encoding performance. Due to the difference in texture and other characteristics of the image, the effect of upsampling can be effectively improved by using multiple filters.

At present, there is a known upsampling technique using multiple filters, which calculates the binary values of the horizontal and vertical directions of the four pixels at positions 1, 2, 3, and 4 for each 4×4 image block. First-order difference, add the second-order difference of four pixels in the horizontal direction, as horizontal (horizontal), add the second-order difference of four pixels in the vertical direction, as vertical (vertical). Thus, the texture direction can be determined. For example, if the vertical is greater than twice the horizontal, the direction is determined to be 1; if the horizontal is greater than twice the vertical, the direction is determined to be 2; if the vertical is equal to twice the horizontal, the direction is determined to be 0. After that, calculate the average value of vertical and horizontal to determine the type of the pixel block, and train a filter for each type, so that the trained filter can be very consistent with the corresponding category, but this method needs to be encoded The terminal encodes the coefficients of the filter and the index (index) of the filter used by each type of block and transmits them to the decoding terminal, so that it can be decoded correctly at the decoding terminal. If this method is used to upsample the base layer reconstructed image, too many bits representing filter coefficients and indices need to be transmitted, thereby affecting the coding performance.

Contents of the invention

Embodiments of the present invention provide a method and device for image processing, which can improve the effect and performance of image processing.

In a first aspect, a method for image processing is provided, the method comprising: determining a first training filter according to a non-smooth region image block of an enhancement layer image and a non-smooth region image block of a base layer image, so that the The first training filter satisfies: the difference between the first prediction information determined according to the first training filter and the non-smooth region image block of the base layer image and the first original information determined according to the non-smooth region image block of the enhancement layer image The similarity between satisfies the first preset condition, wherein the base layer image corresponds to the enhancement layer image; according to the first training filter, an alternative upsampling filter is determined, wherein the alternative upsampling filter The device includes the first training filter; from the candidate up-sampling filter, determine the target up-sampling filter; according to the target up-sampling filter and the base layer image block, determine prediction information; according to the prediction information, target The image block is encoded to generate a target code stream, wherein the target image block is located in the enhancement layer image, the base layer image block is located in the base layer image, and the space between the base image block in the base layer image The position corresponds to the spatial position of the target image block in the enhancement layer image.

In a possible implementation manner, the method further includes: determining a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter Satisfy: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the second Preset conditions, wherein the base layer image corresponds to the enhancement layer image; and determining a candidate upsampling filter according to the first training filter further includes: according to the first training filter and the first training filter Two training filters, determining a candidate upsampling filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

With reference to the first aspect and the first possible implementation manner, in a second possible implementation manner, determining the target upsampling filter from the candidate upsampling filters includes: according to the characteristics of the base layer image block information to determine the smoothness of the target image, wherein the feature information includes the coding block marking information of the base layer image block or the residual information of the base layer image block; according to the smoothness of the target image block, determine the target Upsampling filter.

With reference to the first aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, according to the first training filter and the second training filter, determine the alternative upper A sampling filter, further comprising: determining a candidate upsampling filter based on the first training filter, the second training filter, and a legacy filter, wherein the candidate upsampling filter includes the first training filter , the second training filter and the conventional filter; and performing encoding processing on the target image block according to the prediction information to generate a target code stream, including: performing encoding processing on the target image block according to the prediction information , to generate a target code stream, the target code stream includes first indication information used to indicate the target upsampling filter, and the first indication information is used to obtain the target upsampling filter when decoding the above-mentioned coded target image block The basis for the filter.

With reference to the first aspect, the first possible implementation manner, the second possible implementation manner and the third possible implementation manner, in a fourth possible implementation manner, according to the first training filter, determine the Selecting an upsampling filter further includes: determining a candidate upsampling filter according to the first training filter and the traditional filter, wherein the candidate upsampling filter includes the first training filter and the traditional filter and determining the target up-sampling filter, including: determining the texture degree of the target image block; and determining the target up-sampling filter according to the texture degree of the target image block.

In a second aspect, a method for image processing is provided, the method comprising: determining a first training filter according to a non-smooth region image block of an enhancement layer image and a non-smooth region image block of a base layer image, so that the The first training filter satisfies: the difference between the first prediction information determined according to the first training filter and the non-smooth region image block of the base layer image and the first original information determined according to the non-smooth region image block of the enhancement layer image The similarity between satisfies the first preset condition, wherein the base layer image corresponds to the enhancement layer image; according to the first training filter, an alternative upsampling filter is determined, wherein the alternative upsampling filter The filter includes the first training filter; from among the candidate upsampling filters, a target upsampling filter is determined, the candidate upsampling filter including the first training filter; according to the target upsampling filter and the base layer An image block is used to determine prediction information; according to the prediction information and the residual information obtained from the target code stream, the target code stream is decoded to obtain the target image block, wherein the target image block is located in the enhancement layer image wherein, the base layer image block is located in the base layer image, and the spatial position of the base image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

In a possible implementation manner, the method further includes: determining a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter Satisfy: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the second Preset conditions, wherein the base layer image corresponds to the enhancement layer image; and determining a candidate upsampling filter according to the first training filter further includes: according to the first training filter and the first training filter Two training filters, determining a candidate upsampling filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

With reference to the second aspect and the first possible implementation manner, in the second possible implementation manner, from the candidate upsampling filters, the target upsampling filter is determined from the candidate upsampling filters, The method includes: determining the smoothness of the target image according to the feature information of the base layer image block, wherein the feature information includes coding block marking information of the base layer image block or residual information of the base layer image block; according to the The smoothness of the target image block, which determines the target upsampling filter.

With reference to the second aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, according to the first training filter and the second training filter, determine the alternative upper A sampling filter, further comprising: determining a candidate upsampling filter based on the first training filter, the second training filter, and a legacy filter, wherein the candidate upsampling filter includes the first training filter , the second training filter and the traditional filter; and determining the target up-sampling filter from the candidate up-sampling filters, including: obtaining the information used to indicate the target up-sampling filter from the target code stream The target upsampling filter is determined according to the first indication information.

With reference to the second aspect, the first possible implementation manner, the second possible implementation manner, and the third possible implementation manner, in a fourth possible implementation manner, according to the first training filter, determine the Selecting an upsampling filter further includes: determining a candidate upsampling filter according to the first training filter and the traditional filter, wherein the candidate upsampling filter includes the first training filter and the traditional filter and determining the target up-sampling filter, including: determining the texture degree of the target image block; and determining the target up-sampling filter according to the texture degree of the target image block.

In a third aspect, an apparatus for image processing is provided, which includes: an acquisition unit configured to determine a first training filter according to an image block in a non-smooth area of an enhancement layer image and an image block in an unsmooth area of a base layer image device, so that the first training filter satisfies: the first prediction information determined according to the first training filter and the non-smooth area image block of the base layer image and the non-smooth area image block of the enhancement layer image The similarity between the first original information satisfies a first preset condition, wherein the base layer image corresponds to the enhancement layer image; the determining unit determines an alternative upsampling filter according to the first training filter, Wherein, the candidate upsampling filter includes the first training filter; it is used to determine the target upsampling filter from the candidate upsampling filter; an encoding unit is used to obtain the upsampling filter from the determination unit device, and determine prediction information according to the target upsampling filter and the base layer image block; for encoding the target image block according to the prediction information, so as to generate a target code stream, wherein the target image block is located in the enhanced In the layer image, the base layer image block is located in the base layer image, and the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

In a possible implementation manner, the obtaining unit is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter The filter satisfies: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the first Two preset conditions, wherein the base layer image corresponds to the enhancement layer image; and the determining unit is further used to determine an alternative upsampling filter according to the first training filter and the second training filter, Wherein, the candidate upsampling filter includes the first training filter and the second training filter.

With reference to the third aspect and the first possible implementation manner, in a second possible implementation manner, the determining unit is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, wherein the The feature information includes coded block marking information of the base layer image block or residual information of the base layer image block; it is used to determine the target upsampling filter according to the smoothness of the target image block.

With reference to the third aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, the determining unit is further configured to filter and a traditional filter, determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter, the second training filter, and the traditional filter; and the coding unit is specifically used to According to the prediction information, the target image block is encoded to generate a target code stream, and the target code stream includes first indication information used to indicate the target upsampling filter, and the first indication information is used for decoding the above-mentioned The coded target image block is used as the basis for obtaining the target upsampling filter.

With reference to the third aspect, the first possible implementation manner, the second possible implementation manner and the third possible implementation manner, in a fourth possible implementation manner, the determining unit is further configured to filter and traditional filter, determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter and the traditional filter; specifically used to determine the texture of the target image block; The target up-sampling filter is determined according to the texture degree of the target image block.

In a fourth aspect, there is provided an image processing device, which is characterized in that the device includes: an acquisition unit, configured to determine according to the non-smooth region image block of the enhancement layer image and the non-smooth region image block of the base layer image The first training filter, so that the first training filter satisfies: the first prediction information determined according to the first training filter and the non-smooth region image block of the base layer image and according to the non-smooth region of the enhancement layer image The similarity between the first original information determined by the image block satisfies the first preset condition, wherein the base layer image corresponds to the enhancement layer image; the determining unit is configured to determine the backup image according to the first training filter Selecting an upsampling filter, wherein the candidate upsampling filter includes the first training filter; for determining a target upsampling filter from the candidate upsampling filters, the candidate upsampling filter including the A first training filter; a decoding unit, configured to obtain the target upsampling filter from the determination unit, and determine prediction information according to the target upsampling filter and the base layer image block; and to determine prediction information based on the prediction information and the target The residual information obtained in the code stream is decoded on the target code stream to obtain the target image block, wherein the target image block is located in the enhancement layer image, and the base layer image block is located in the base layer image, And the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

In a possible implementation manner, the obtaining unit is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter The filter satisfies: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the first Two preset conditions, wherein the base layer image corresponds to the enhancement layer image; and the determining unit is further used to determine an alternative upsampling filter according to the first training filter and the second training filter, Wherein, the candidate upsampling filter includes the first training filter and the second training filter.

With reference to the fourth aspect and the first possible implementation manner, in a second possible implementation manner, the determining unit is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, wherein the The feature information includes coded block marking information of the base layer image block or residual information of the base layer image block; and the target upsampling filter is determined according to the smoothness of the target image block.

With reference to the fourth aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, the determining unit is further configured to filter and traditional filter, determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter, the second training filter and the traditional filter; In the method, the first indication information used to indicate the target up-sampling filter is acquired, and is used to determine the target up-sampling filter according to the first indication information.

With reference to the fourth aspect, the first possible implementation manner, the second possible implementation manner and the third possible implementation manner, in a fourth possible implementation manner, the determining unit is further configured to A filter and a traditional filter, determining an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter and the traditional filter; used to determine the texture degree of the target image block; used to The target upsampling filter is determined according to the texture degree of the target image block.

In a fifth aspect, an encoder for image processing is provided, and the encoder includes: a bus; a processor connected to the bus; a memory connected to the bus; wherein, the processor calls the memory through the bus The program stored in is used to determine a first training filter according to the non-smooth area image blocks of the enhancement layer image and the non-smooth area image blocks of the base layer image, so that the first training filter satisfies: according to the first The similarity between the training filter and the first prediction information determined by the non-smooth area image block of the base layer image and the first original information determined by the non-smooth area image block of the enhancement layer image satisfies a first preset condition, Wherein, the base layer image corresponds to the enhancement layer image; according to the first training filter, an alternative upsampling filter is determined, wherein the alternative upsampling filter includes the first training filter; from the In the alternative upsampling filter, determine the target upsampling filter; determine prediction information according to the target upsampling filter and the base layer image block; perform encoding processing on the target image block according to the prediction information to generate a target code stream , wherein the target image block is located in the enhancement layer image, the base layer image block is located in the base layer image, and the spatial position of the base image block in the base layer image is the same as that of the target image block in the enhancement layer image corresponds to the spatial location in .

In a possible implementation manner, the processing unit is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter The filter satisfies: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the first Two preset conditions, wherein the base layer image corresponds to the enhancement layer image; for determining an alternative upsampling filter according to the first training filter and the second training filter, wherein the alternative The upsampling filter includes the first training filter and the second training filter.

With reference to the fifth aspect and the first possible implementation manner, in a second possible implementation manner, the processing unit is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, wherein the The feature information includes coded block marking information of the base layer image block or residual information of the base layer image block; it is used to determine the target upsampling filter according to the smoothness of the target image block.

With reference to the fifth aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, the processor is specifically configured to filter and a traditional filter, and determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter, the second training filter, and the traditional filter; for according to the prediction information, Encoding the target image block to generate a target code stream, the target code stream includes first indication information used to indicate the target upsampling filter, and the first indication information is used to decode the encoded target image block time as the basis for obtaining the target upsampling filter

With reference to the fifth aspect, the first possible implementation manner, the second possible implementation manner and the third possible implementation manner, in a fourth possible implementation manner, the processor is specifically configured to filter and traditional filter, determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter and the traditional filter; specifically used to determine the texture of the target image block; The target up-sampling filter is determined according to the texture degree of the target image block. .

In a sixth aspect, there is provided a decoder for image processing, the decoder comprising: a bus; a processor connected to the bus; a memory connected to the bus; wherein, the processor calls the memory through the bus The program stored in is used to determine a first training filter according to the non-smooth area image blocks of the enhancement layer image and the non-smooth area image blocks of the base layer image, so that the first training filter satisfies: according to the first The similarity between the training filter and the first prediction information determined by the non-smooth area image block of the base layer image and the first original information determined by the non-smooth area image block of the enhancement layer image satisfies a first preset condition, Wherein, the base layer image corresponds to the enhancement layer image; according to the first training filter, a candidate upsampling filter is determined, wherein the candidate upsampling filter includes the first training filter; from the backup In the selected upsampling filter, determine the target upsampling filter, the candidate upsampling filter includes the first training filter; according to the target upsampling filter and the base layer image block, determine prediction information; according to the prediction information and the residual information obtained from the target code stream, the target code stream is decoded to obtain the target image block, wherein the target image block is located in the enhancement layer image, and the base layer image block is located in the base layer image, and the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

In a possible implementation manner, the processing unit is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter The filter satisfies: the similarity between the second prediction information determined according to the second training filter and the smooth region image block of the base layer image and the second original information determined according to the smooth region image block of the enhancement layer image satisfies the first Two preset conditions, wherein the base layer image corresponds to the enhancement layer image; for determining an alternative upsampling filter according to the first training filter and the second training filter, wherein the alternative The upsampling filter includes the first training filter and the second training filter.

With reference to the sixth aspect and the first possible implementation manner, in a second possible implementation manner, the processing unit is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, wherein the The feature information includes coded block marking information of the base layer image block or residual information of the base layer image block; and the target upsampling filter is determined according to the smoothness of the target image block.

With reference to the sixth aspect, the first possible implementation manner, and the second possible implementation manner, in a third possible implementation manner, the processor is further configured to filter and traditional filter, determine an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter, the second training filter and the traditional filter; In the method, the first indication information used to indicate the target up-sampling filter is acquired, and is used to determine the target up-sampling filter according to the first indication information.

With reference to the sixth aspect, the first possible implementation manner, the second possible implementation manner and the third possible implementation manner, in a fourth possible implementation manner, the processor is further configured to A filter and a traditional filter, determining an alternative upsampling filter, wherein the alternative upsampling filter includes the first training filter and the traditional filter; used to determine the texture degree of the target image block; used to The target upsampling filter is determined according to the texture degree of the target image block.

According to the method for image processing, the device encoder and the decoder of the embodiments of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, it is possible to reduce the number of upsampling filters while improving the effect of upsampling. There is no need to transmit filter coefficients and indexes, so that the encoding performance can be improved, and the effect and performance of image processing can be improved.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required in the embodiments of the present invention. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without making creative efforts.

Fig. 1 is a schematic flowchart of a method for image processing according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a method for determining a training filter according to an embodiment of the present invention.

Fig. 3 is another schematic flowchart of a method for image processing according to an embodiment of the present invention.

Fig. 4 is a schematic block diagram of an apparatus for image processing according to an embodiment of the present invention.

Fig. 5 is a schematic block diagram of an apparatus for image processing according to another embodiment of the present invention.

Fig. 6 is a schematic block diagram of an encoder for image processing according to an embodiment of the present invention.

Fig. 7 is a schematic block diagram of a decoder for image processing according to another embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Fig. 1 shows a schematic flowchart of a method 100 for image processing according to an embodiment of the present invention described from the perspective of an encoding end. As shown in Figure 1, the method 100 includes:

S110. Determine a first training filter according to the non-smooth region image block of the enhancement layer image and the non-smooth region image block of the base layer image, so that the first training filter satisfies: according to the first training filter and the basic The similarity between the first prediction information determined by the image block in the non-smooth area of the layer image and the first original information determined based on the image block in the non-smooth area of the enhancement layer image satisfies a first preset condition, wherein the base layer an image corresponding to the enhancement layer image;

S120. Determine a candidate upsampling filter according to the first training filter, where the candidate upsampling filter includes the first training filter;

S130. Determine a target upsampling filter from the candidate upsampling filters;

S140. Determine prediction information according to the target upsampling filter and the base layer image block.

S150. Perform encoding processing on the target image block according to the prediction information to generate a target code stream, wherein the target image block is located in the enhancement layer image, the base layer image block is located in the base layer image, and the base image The spatial position of the block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image

In the layered coding of images, for example, in spatially scalable coding, the resolution of the image can be processed to obtain a low-resolution image. As a comparison, the original image is called a high-resolution image, and the encoder separately converts the low-resolution The high-resolution image and the high-resolution image are encoded. For convenience of description, a high-quality image to be encoded is referred to as an enhancement layer image, and a corresponding low-quality image to be encoded (for example, the low-resolution image) is referred to as a base layer image.

In the embodiment of the present invention, the target image is an image processed using layered coding technology, and the basic layer refers to the quality in layered coding (including frame rate, spatial resolution, temporal resolution, signal-to-noise ratio strength or quality level and other parameters), the enhancement layer refers to the layer with higher quality (including parameters such as frame rate, spatial resolution, time resolution, signal-to-noise ratio strength or quality level) in layered coding. It should be noted that, in the embodiment of the present invention, in the embodiment of the present invention, for a given enhancement layer, the corresponding base layer may be any layer whose quality is lower than the enhancement layer, for example, if the current There are five layers, and the encoding quality increases in order (that is, the first layer has the lowest quality, the fifth layer has the highest quality), and if the enhancement layer is the fourth layer, the base layer can be the first layer, or the second layer, or It could be the third layer, or it could be the fourth layer. Similarly, for a given base layer, the corresponding enhancement layer may be any layer whose quality is lower than the base layer.

The enhancement layer image is an image in the currently processed enhancement layer, and the base layer image is an image in the base layer at the same moment as the enhancement layer image.

To sum up, in the embodiment of the present invention, the quality of the base layer image is lower than the quality of the enhancement layer image.

The target image block is an image block being processed in the enhancement layer image.

The base layer image block is an image block in the base layer image corresponding to the target image block in spatial position.

In the embodiment of the present invention, the corresponding relationship between the base layer image block and the target image block can be calculated according to the resolution ratio relationship between the base layer image and the enhancement layer image. For example, in a system including x direction and y direction, if the resolution of the enhancement layer image in the x direction and y direction is twice that of the base layer image respectively, then the pixel coordinates of the upper left corner in the enhancement layer are (2x, 2y ) with a size of (2m)×(2n), the corresponding block in the base layer image can be an image block whose pixel coordinates in the upper left corner are (x, y) and whose size is m×n.

In the embodiment of the present invention, an image (including an enhancement layer image and a base layer image) is divided into two simple types of regions, namely, a smooth region and a non-smooth region. In the smooth area, a relatively accurate prediction value can usually be obtained during encoding, so that the coded block flag (CBF, CodedBlock Flag) determined during final encoding is 0, that is, the residual is 0. In the non-smooth area, due to the small correlation of signal characteristics during encoding, it is impossible to predict accurately, so a more accurate prediction value cannot be obtained, resulting in large or uneven residual after prediction, so that the final encoded CBF is not 0.

Therefore, in the embodiment of the present invention, it can be determined that the image block with a CBF of 0 in the base layer image (the image block in the smooth area of the base layer image) is located in the smooth area, and thus, it can be considered that the image block corresponding to the image block in the enhancement layer image The image blocks (smooth area image blocks of the enhancement layer image) are located in the smooth area. Similarly, it can be determined that the image block in the base layer image whose CBF is not 0 (the image block in the non-smooth area of the base layer image) is located in the non-smooth area, so that the image block in the enhancement layer image corresponding to this image block can be considered (A non-smooth region image block of an enhancement layer image) is located in a non-smooth region. As described above, smooth area image blocks of the enhancement layer image and smooth area image blocks of the base layer image, and non-smooth area image blocks of the enhancement layer image and non-smooth area image blocks of the base layer image may be determined.

Thereafter, at S110, the first training filter may be trained according to the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image. As an example but not a limitation, the first training filter may be trained by the following method Train the filter.

As shown in Figure 2, y1(n) represents the smooth area image block of the enhancement layer image (original image) (a collection of multiple image blocks, hereinafter referred to as the original smooth area image block), and x(n) represents the base layer image H(n) represents the filter to be determined (the first training filter), e(n) represents the smooth region image block of the filtered base layer image (referred to as the predicted image block) and the original Smooth region image patches. For example, to minimize the mean square error of the pixel values of the original smooth region image block and the predicted image block as an optimization condition (an example of the first preset condition), H(n) is solved.

The optimal solution of H(n) can be expressed as the following formula (1),

$\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; xx</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; yx</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, R _xx represents the autocorrelation function of the original smooth region image block, and _ryx represents the cross-correlation function between the smooth region image block of the base layer image and the original smooth region image block.

It should be understood that the methods for obtaining training filters listed above are only illustrative, and the present invention is not limited thereto. For example, various changes may be made to the method for obtaining training filters by changing the above optimization conditions and the like.

Optionally, the method also includes:

According to the smooth region image block of the enhancement layer image and the smooth region image block of the base layer image, determine a second training filter so that the second training filter satisfies: according to the second training filter and the base layer image The similarity between the second prediction information determined based on the smooth area image block of the enhancement layer image and the second original information determined according to the smooth area image block of the enhancement layer image satisfies a second preset condition, wherein the base layer image and the enhancement layer image layer image correspondence; and

According to the first training filter, determining an alternative upsampling filter further includes:

A candidate upsampling filter is determined according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

In the embodiment of the present invention, except that the training samples are different (the first training filter is obtained by training the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image, and the second training filter is the enhancement layer image block The smooth area image block of the image and the smooth area image block of the base layer image are obtained through training), and other processes are similar, and here, in order to avoid redundant description, its description is omitted.

Through the above method, the first training filter and the second training filter can be obtained respectively. Therefore, in the embodiment of the present invention, the coefficients of the training filter are fixed, and there is no need to consume bit transmission filter coefficients in the encoding process. At the same time, when selecting a filter at the decoding end, for example, the type of the current block (that is, an image block in a smooth area or an image block in a non-smooth area) can be judged according to the CBF value of the corresponding block in the base layer, so that there is no need to transmit each image block using The index of the filter improves the performance of image processing.

Therefore, the candidate filter may include the first training filter and the second training filter, that is, case 1.

Case 1

Optionally, the target upsampling filter is determined from the alternative upsampling filters, including:

determining the smoothness of the target image according to feature information of the base layer image block, wherein the feature information includes coding block marking information of the base layer image block or residual information of the base layer image block;

The target upsampling filter is determined according to the smoothness of the target image block.

Specifically, in the case that the candidate upsampling filter includes the first training filter and the second training filter obtained as described above, in S130, according to the type of the target image block (which is a smooth region image blocks or non-smooth region image blocks), select the target upsampling filter.

In the embodiment of the present invention, when the CBF of the base layer image block corresponding to the target image block is 0, it may be determined that the target image block is located in a smooth area. Similarly, when the CBF of the base layer image block corresponding to the target image block is not 0, it can be determined that the target image block is located in a non-smooth area.

It should be understood that the method for determining the smoothness of the target image block and the parameters used above are only exemplary, and the present invention is not limited thereto. Others can determine the smoothness of the target image block, that is, determine that the target image block is in The methods and parameters for enhancing the smooth area or non-smooth area in the image of the layer fall within the protection scope of the present invention.

In this case, at S140, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter determined as described above, so as to determine a prediction value relative to the target image block.

Therefore, at S150, the distortion rate cost of each prediction mode can be calculated, and the optimal prediction mode used when encoding the target image block can be determined. It should be noted that, when decoding the encoded target image block, the same method as above can be used to determine the target up-sampling filter.

Optionally, the alternative upsampling filter also includes a conventional filter, and

According to the prediction information, the target image block is encoded to generate a target code stream, including:

According to the prediction information, the target image block is encoded to generate a target code stream, and the target code stream includes first indication information used to indicate the target upsampling filter, and the first indication information is used for decoding the above-mentioned The coded target image block is used as the basis for obtaining the target upsampling filter.

In the embodiment of the present invention, as a traditional filter, for example, an existing cosine interpolation filter may be included. In the following description, for ease of description, the conventional filter is taken as an example of a cosine interpolation filter for description.

Specifically, in the embodiment of the present invention, the above-mentioned method for obtaining the training filter (training process) is performed in the pixel domain, and can be used for different downsampling ratios (the resolution ratio between the enhancement layer image and the base layer image) ) for different training, for example, there are cases where the filters obtained for integer pixel positions and half pixel positions are different, therefore, it may lead to unbalanced predictions for integer pixel positions and half pixel positions, thus affecting the stability of the prediction residual Therefore, in the embodiment of the present invention, a traditional filter, such as a cosine interpolation filter, can also be added to the alternative upsampling filter, and the acquisition method of the cosine interpolation filter can be the same as that of the prior art, Here, in order to avoid redundant description, its description is omitted.

Therefore, the candidate filter may include the first training filter and the second training filter and a cosine interpolation filter (an example of a traditional filter), that is, case 2.

Case 2

In S130, for example, rate-distortion optimization (RDO, Rate-Distortion Optimization) may be used to select to use a cosine interpolation filter or the first training filter or the second training filter as the target up-sampling filter.

In this case, thereafter, at S140, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter, so as to determine a prediction value relative to the target image block.

Therefore, at S150, the distortion rate cost of each prediction mode can be calculated, and the optimal prediction mode used when encoding the target image block can be determined. When the optimal prediction mode is an inter-layer texture prediction mode, the target upsampling filter (specifically, indicating that the target upsampling filter is a cosine interpolation filter, the first training filter or which filter in the first training filter) encodes the first indication information, and adds the encoded first indication information to the code stream, so as to obtain the target when decoding the above-mentioned encoded target image block Upsampling filter basis. It should be noted that when the candidate filter includes the cosine interpolation filter or the first training filter or the second training filter as the target upsampling filter, there are three candidate filters, and, as mentioned above The encoding end or the decoding end can determine to use the first training filter or the second training filter according to the smoothness of the target image block. Therefore, only one bit identifier can be used to carry the first indication information in the code stream, so as to Indicates whether this target upsampling filter is a legacy filter (cosine interpolation filter) or a training filter (first training filter or second training filter). When there are at least two traditional filters among the candidate filters, the purpose of indicating the target image block can be achieved by increasing the number of bits of the first indication information.

When upsampling through a cosine interpolation filter, the corresponding pixels of the base layer image are always copied directly, but, for example, in scalable video coding methods, the pixels of the base layer image are not directly copied from the corresponding enhancement layer image At this time, if the entire pixel of the target image is located at the mutation point, a large error will occur when directly copying the corresponding pixel of the base layer when performing upsampling. Therefore, using this method for upsampling may cause a large error in the integer pixel position of the enhancement layer image. Therefore, in the embodiment of the present invention, the pixels obtained by using the method of the embodiment of the present invention to train the above-mentioned mutation points The training filter (the first training filter or the second training filter) can improve the effect of upsampling and improve the performance of encoding and image processing.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The determined target upsampling filter, including:

Determine the texture degree of the target image block;

The target upsampling filter is determined according to the texture degree of the target image block.

As mentioned above, in the implementation of the present invention, in the case where the candidate upsampling filter includes a cosine interpolation filter, a first training filter and a second training filter. As mentioned above, after selecting the target upsampling filter according to RDO, it is necessary to transmit the flag bit used to carry the coded first indication information in the code stream, so as to determine the target upsampling when decoding the above coded target image block Which filter is the filter. Therefore, in this solution, two candidate filters can be used, but they are not selected through the RDO, but are selected according to different characteristics of different filters, so as to avoid transmitting an extra flag bit to indicate the target upsampling filter. That is, the candidate filter includes the first training filter and the traditional filter, i.e. case 3

Case 3

In S130, for example, the target upsampling filter may be selected from the first training filter and the cosine interpolation filter (an example of a traditional filter) according to the feature information of the base layer image block, thereby avoiding the transmission of the The filter, for example, can be used to determine the selected filter according to the texture strength of the base layer image block. In the embodiment of the present invention, methods such as edge detection, texture strength analysis, or intra-frame coding prediction mode can be used, Determine the texture of the base layer image block, and, for example, when the texture is strong, choose to use the filter obtained from training as the target upsampling filter, and use the cosine interpolation filter for the rest. The method for determining the texture degree of the base layer image block by means of edge detection, texture strength analysis, or intra-frame coding prediction mode listed above may be the same as that of the prior art, and its description is omitted here to avoid redundant description.

In this case, thereafter, at S140, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter, so as to determine a prediction value relative to the target image block.

Therefore, at S150, the distortion rate cost of each prediction mode can be calculated, and the optimal prediction mode used when encoding the target image block can be determined. And encode the target image block.

When upsampling through a cosine interpolation filter, the corresponding pixels of the base layer image are always copied directly, but, for example, in scalable video coding methods, the pixels of the base layer image are not directly copied from the corresponding enhancement layer image At this time, if the entire pixel of the target image is located at the mutation point, a large error will occur when directly copying the corresponding pixel of the base layer when performing upsampling. The first training filter can better restore the pixels at the position of the mutation point, so it can well make up for the deficiency of the cosine interpolation filter.

It should be noted that, when decoding the encoded target image block, the same method as above can be used to determine the target up-sampling filter.

According to the method for image processing in the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and no transmission filter is required The coefficients and indexes can improve the coding performance and improve the effect and performance of image processing.

Fig. 3 shows a schematic flowchart of a method 200 for image processing according to an embodiment of the present invention described from the perspective of an encoding end. As shown in Figure 3, the method 200 includes:

S210. Determine a first training filter according to the non-smooth region image block of the enhancement layer image and the non-smooth region image block of the base layer image, so that the first training filter satisfies: according to the first training filter and the basic The similarity between the first prediction information determined by the image block in the non-smooth area of the layer image and the first original information determined based on the image block in the non-smooth area of the enhancement layer image satisfies a first preset condition, wherein the base layer an image corresponding to the enhancement layer image;

S220. Determine a candidate upsampling filter according to the first training filter, where the candidate upsampling filter includes the first training filter;

S230. Determine a target upsampling filter from candidate upsampling filters, where the candidate upsampling filter includes the first training filter;

S240. Determine prediction information according to the target upsampling filter and the base layer image block.

S250. Perform decoding processing on the target code stream according to the prediction information and the residual information obtained from the target code stream to obtain the target image block, wherein the target image block is located in the enhancement layer image, and the base layer The image block is located in the base layer image, and the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image

In the layered coding of images, for example, in spatially scalable coding, the resolution of the image can be processed to obtain a low-resolution image. As a comparison, the original image is called a high-resolution image, and the encoder separately converts the low-resolution The high-resolution image and the high-resolution image are encoded. For convenience of description, a high-quality image to be encoded is referred to as an enhancement layer image, and a corresponding low-quality image to be encoded (for example, the low-resolution image) is referred to as a base layer image.

In the embodiment of the present invention, the target image is an image processed using layered coding technology, and the basic layer refers to the quality in layered coding (including frame rate, spatial resolution, temporal resolution, signal-to-noise ratio strength or quality level and other parameters), the enhancement layer refers to the layer with higher quality (including parameters such as frame rate, spatial resolution, time resolution, signal-to-noise ratio strength or quality level) in layered coding. It should be noted that, in the embodiment of the present invention, in the embodiment of the present invention, for a given enhancement layer, the corresponding base layer may be any layer whose quality is lower than the enhancement layer, for example, if the current There are five layers, and the encoding quality increases in order (that is, the first layer has the lowest quality, the fifth layer has the highest quality), and if the enhancement layer is the fourth layer, the base layer can be the first layer, or the second layer, or It could be the third layer, or it could be the fourth layer. Similarly, for a given base layer, the corresponding enhancement layer may be any layer whose quality is lower than the base layer.

The enhancement layer image is an image in the currently processed enhancement layer, and the base layer image is an image in the base layer at the same time as the enhancement layer image.

To sum up, in the embodiment of the present invention, the quality of the base layer image is lower than the quality of the enhancement layer image.

The target image block is an image block being processed in the enhancement layer image.

The base layer image block is an image block in the base layer image corresponding to the target image block in spatial position.

In the embodiment of the present invention, the corresponding relationship between the base layer image block and the target image block can be calculated according to the resolution ratio relationship between the base layer image and the enhancement layer image. For example, in a system including x direction and y direction, if the resolution of the enhancement layer image in the x direction and y direction is twice that of the base layer image respectively, then the pixel coordinates of the upper left corner in the enhancement layer are (2x, 2y ) with a size of (2m)×(2n), the corresponding block in the base layer image can be an image block whose pixel coordinates in the upper left corner are (x, y) and whose size is m×n.

In the embodiment of the present invention, an image (including an enhancement layer image and a base layer image) is divided into two simple types of regions, namely, a smooth region and a non-smooth region. In the smooth area, a relatively accurate prediction value can usually be obtained during encoding, so that the coded block flag (CBF, Coded Block Flag) determined during final encoding is 0, that is, the residual is 0. In the non-smooth area, due to the small correlation of signal characteristics during encoding, it is impossible to predict accurately, so a more accurate prediction value cannot be obtained, resulting in large or uneven residual after prediction, so that the final encoded CBF is not 0.

Therefore, in the embodiment of the present invention, it can be determined that the image block with a CBF of 0 in the base layer image (the image block in the smooth area of the base layer image) is located in the smooth area, and thus, it can be considered that the image block corresponding to the image block in the enhancement layer image The image blocks (smooth area image blocks of the enhancement layer image) are located in the smooth area. Similarly, it can be determined that the image block in the base layer image whose CBF is not 0 (the image block in the non-smooth area of the base layer image) is located in the non-smooth area, so that the image block in the enhancement layer image corresponding to this image block can be considered (A non-smooth region image block of an enhancement layer image) is located in a non-smooth region. As described above, smooth area image blocks of the enhancement layer image and smooth area image blocks of the base layer image, and non-smooth area image blocks of the enhancement layer image and non-smooth area image blocks of the base layer image may be determined.

Thereafter, at S210, the first training filter may be trained according to the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image. As an example but not a limitation, the first training filter may be trained by the following method Train the filter.

As shown in Figure 2, y1(n) represents the smooth area image block of the enhancement layer image (original image) (a collection of multiple image blocks, hereinafter referred to as the original smooth area image block), and x(n) represents the base layer image H(n) represents the filter to be determined (the first training filter), e(n) represents the smooth region image block of the filtered base layer image (referred to as the predicted image block) and the original Smooth region image patches. For example, to minimize the mean square error of the pixel values of the original smooth region image block and the predicted image block as an optimization condition (an example of the first preset condition), H(n) is solved.

The optimal solution of H(n) can be expressed as the above formula (1),

It should be understood that the methods for obtaining training filters listed above are only illustrative, and the present invention is not limited thereto. For example, various changes may be made to the method for obtaining training filters by changing the above optimization conditions and the like.

Optionally, the method also includes:

According to the smooth region image block of the enhancement layer image and the smooth region image block of the base layer image, determine a second training filter so that the second training filter satisfies: according to the second training filter and the base layer image The similarity between the second prediction information determined based on the smooth area image block of the enhancement layer image and the second original information determined according to the smooth area image block of the enhancement layer image satisfies a second preset condition, wherein the base layer image and the enhancement layer image layer image correspondence; and

According to the first training filter, determining an alternative upsampling filter further includes:

A candidate upsampling filter is determined according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

In the embodiment of the present invention, except that the training samples are different (the first training filter is obtained by training the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image, and the second training filter is the enhancement layer image block The smooth area image block of the image and the smooth area image block of the base layer image are obtained through training), and other processes are similar, and here, in order to avoid redundant description, its description is omitted.

Through the above method, the first training filter and the second training filter can be obtained respectively. Therefore, in the embodiment of the present invention, the coefficients of the training filter are fixed, and there is no need to consume bit transmission filter coefficients in the encoding process. At the same time, when selecting a filter at the decoding end, for example, the type of the current block (that is, an image block in a smooth area or an image block in a non-smooth area) can be judged according to the CBF value of the corresponding block in the base layer, so that there is no need to transmit each image block using The index of the filter improves the performance of image processing.

Therefore, the candidate filter may include the first training filter and the second training filter, that is, case 4.

Case 4

Optionally, the target upsampling filter is determined from the alternative upsampling filters, including:

determining the smoothness of the target image according to feature information of the base layer image block, wherein the feature information includes coding block marking information of the base layer image block or residual information of the base layer image block;

The target upsampling filter is determined according to the smoothness of the target image block.

Specifically, in the case where the candidate upsampling filter includes the first training filter and the second training filter obtained as described above, in S230, according to the type of the target image block (which is a smooth region image block or non-smooth region image blocks), select the target upsampling filter.

In the embodiment of the present invention, when the CBF of the base layer image block corresponding to the target image block is 0, it may be determined that the target image block is located in a smooth region. Similarly, when the CBF of the base layer image block corresponding to the target image block is not 0, it can be determined that the target image block is located in a non-smooth area.

It should be understood that the method for determining the smoothness of the target image block and the parameters used above are only exemplary, and the present invention is not limited thereto. Others can determine the smoothness of the target image block, that is, determine that the target image block is in The methods and parameters for enhancing the smooth area or non-smooth area in the image of the layer fall within the protection scope of the present invention.

In this case, at S240, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter determined as described above, so as to determine a prediction value relative to the target image block.

Therefore, at S250, the target image block can be decoded according to the predicted value and the residual information obtained from the target code stream. In the embodiment of the present invention, this process can be the same as that of the prior art. To avoid redundant description, here Its description is omitted.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The target upsampling filter is determined from the alternative upsampling filters, including:

From the target code stream, acquire first indication information for indicating the target upsampling filter,

Determine the target upsampling filter according to the first indication information.

In the embodiment of the present invention, as a traditional filter, for example, an existing cosine interpolation filter may be included. In the following description, for ease of description, the conventional filter is taken as an example of a cosine interpolation filter for description.

Specifically, in the embodiment of the present invention, the above-mentioned method for obtaining the training filter (training process) is performed in the pixel domain, and can be used for different downsampling ratios (the resolution ratio between the enhancement layer image and the base layer image) ) for different training, for example, there are cases where the filters obtained for integer pixel positions and half pixel positions are different, therefore, it may lead to unbalanced predictions for integer pixel positions and half pixel positions, thus affecting the stability of the prediction residual Therefore, in the embodiment of the present invention, a traditional filter, such as a cosine interpolation filter, can also be added to the alternative upsampling filter, and the acquisition method of the cosine interpolation filter can be the same as that of the prior art, Here, in order to avoid redundant description, its description is omitted.

Therefore, the candidate filter may include the first training filter and the second training filter and a cosine interpolation filter (an example of a traditional filter), that is, case 5.

Case 5

In S230, for example, the first indication information may be obtained from the target code stream. In this embodiment of the present invention, the alternative filter includes the cosine interpolation filter or the first training filter or the second training filter, as When the target upsampling filter is used, there are three alternative filters, and, as described above, the encoding end or the decoding end can determine to use the first training filter or the second training filter according to the smoothness of the target image block. Therefore, Only one bit identifier can be used in the code stream to carry the first indication information to indicate whether the target upsampling filter is a traditional filter (cosine interpolation filter) or a training filter (first training filter or second training filter). For example, when the indication information is 1, select the training filter (including the first training filter or the second training filter), and according to the smoothness of the target image block, from the first training filter or the second training filter The target upsampling filter is determined in the filter. For example, when the indication information is 0, the cosine interpolation filter is selected as the target upsampling filter.

It should be understood that the method for indicating the target upsampling filter by using the first indication information listed above is only an exemplary description, and the present invention is not limited thereto.

It should be noted that when the number of conventional filters in the candidate filters is at least two, the purpose of indicating the target image block can be achieved by increasing the number of bits of the first indication information.

In this case, at S240, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter determined as described above, so as to determine a prediction value relative to the target image block.

Therefore, at S250, the target image block can be decoded according to the predicted value and the residual information obtained from the target code stream. In the embodiment of the present invention, this process can be the same as that of the prior art. To avoid redundant description, here Its description is omitted.

When upsampling through a cosine interpolation filter, the corresponding pixels of the base layer image are always copied directly, but, for example, in scalable video coding methods, the pixels of the base layer image are not directly copied from the corresponding enhancement layer image At this time, if the entire pixel of the target image is located at the mutation point, a large error will occur when directly copying the corresponding pixel of the base layer when performing upsampling. Therefore, using this method for upsampling may cause a large error in the integer pixel position of the enhancement layer image. Therefore, in the embodiment of the present invention, the pixels obtained by using the method of the embodiment of the present invention to train the above-mentioned mutation points The training filter (the first training filter or the second training filter) can improve the effect of upsampling and improve the performance of encoding and image processing.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The determined target upsampling filter, including:

Determine the texture degree of the target image block;

The target upsampling filter is determined according to the texture degree of the target image block.

As mentioned above, in the implementation of the present invention, in the case where the candidate upsampling filter includes a cosine interpolation filter, a first training filter and a second training filter. As mentioned above, after selecting the target upsampling filter according to RDO, it is necessary to transmit the flag bit used to carry the coded first indication information in the code stream, so as to determine the target upsampling when decoding the above coded target image block Which filter is the filter. Therefore, in this solution, two candidate filters can be used, but they are not selected through the RDO, but are selected according to different characteristics of different filters, so as to avoid transmitting an extra flag bit to indicate the target upsampling filter. That is, the candidate filter includes the first training filter and the traditional filter, i.e. case 6

Case 6

In S230, for example, the target upsampling filter may be selected from the first training filter and the cosine interpolation filter (an example of a traditional filter) according to the feature information of the base layer image block, thereby avoiding the transmission of the The filter, for example, can be used to determine the selected filter according to the texture strength of the base layer image block. In the embodiment of the present invention, methods such as edge detection, texture strength analysis, or intra-frame coding prediction mode can be used, Determine the texture of the base layer image block, and, for example, when the texture is strong, choose to use the filter obtained from training as the target upsampling filter, and use the cosine interpolation filter for the rest. The method for determining the texture degree of the base layer image block by means of edge detection, texture strength analysis, or intra-frame coding prediction mode listed above may be the same as that of the prior art, and its description is omitted here to avoid redundant description.

In this case, at S240, the reconstructed image of the base layer image block may be up-sampled according to the target up-sampling filter determined as described above, so as to determine a prediction value relative to the target image block.

Therefore, at S250, the target image block can be decoded according to the predicted value and the residual information obtained from the target code stream. In the embodiment of the present invention, this process can be the same as that of the prior art. To avoid redundant description, here Its description is omitted.

When upsampling through a cosine interpolation filter, the corresponding pixels of the base layer image are always copied directly, but, for example, in scalable video coding methods, the pixels of the base layer image are not directly copied from the corresponding enhancement layer image At this time, if the entire pixel of the target image is located at the mutation point, a large error will occur when directly copying the corresponding pixel of the base layer when performing upsampling. The first training filter can better restore the pixels at the position of the mutation point, so it can well make up for the deficiency of the cosine interpolation filter.

According to the method for image processing in the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and no transmission filter is required The coefficients and indexes can improve the coding performance and improve the effect and performance of image processing.

Above, the method for image processing according to the embodiment of the present invention is described in detail with reference to FIGS. .

Fig. 4 shows a schematic block diagram of an apparatus 300 for image processing according to an embodiment of the present invention. As shown in Figure 7, the device 300 includes:

The obtaining unit 310 is configured to determine a first training filter according to the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image, so that the first training filter satisfies: according to the first training filter The similarity between the first prediction information determined by the detector and the non-smooth area image block of the base layer image and the first original information determined according to the non-smooth area image block of the enhancement layer image satisfies a first preset condition, wherein, The base layer image corresponds to the enhancement layer image;

A determining unit 320, configured to determine a candidate upsampling filter according to the first training filter, where the candidate upsampling filter includes the first training filter;

For determining a target upsampling filter from the candidate upsampling filters, and transmitting the target upsampling filter to the encoding unit 330, the candidate upsampling filter includes the first training obtained by the obtaining unit 310 filter;

An encoding unit 330, configured to obtain the upsampling filter from the determination unit, and determine prediction information according to the target upsampling filter and the base layer image block;

is used to encode the target image block according to the prediction information to generate a target code stream, wherein the target image block is located in the enhancement layer image, the base layer image block is located in the base layer image, and the base image The spatial position of the block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

Optionally, the obtaining unit 310 is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter satisfies: according to The similarity between the second training filter and the second prediction information determined by the smooth area image block of the base layer image and the second original information determined by the smooth area image block of the enhancement layer image satisfies a second preset condition , where the base layer image corresponds to the enhancement layer image; and

The determining unit 320 is further configured to determine a candidate upsampling filter according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter Train the filter.

Optionally, the determining unit 320 is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, where the feature information includes coding block label information of the base layer image block or the base layer image block The residual information of the image block;

It is used to determine the target up-sampling filter according to the smoothness of the target image block.

Optionally, the determining unit 320 is further configured to determine a candidate upsampling filter according to the first training filter, the second training filter and the traditional filter, wherein the candidate upsampling filter includes the first training filter a training filter, the second training filter, and the legacy filter; and

The encoding unit 330 is specifically configured to perform encoding processing on the target image block according to the prediction information to generate a target code stream, and the target code stream includes first indication information for indicating the target upsampling filter, the first The indication information is used as a basis for obtaining the target up-sampling filter when decoding the encoded target image block.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The determining unit 320 is specifically configured to determine the texture degree of the target image block;

It is used for determining the target up-sampling filter according to the texture degree of the target image block.

According to the device for image processing in the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and no transmission filter is required The coefficients and indexes can improve the coding performance and improve the effect and performance of image processing.

The device 300 for image processing according to the embodiment of the present invention may correspond to the encoding end in the method of the embodiment of the present invention, and each unit in the device 300 for image processing is the module and the above-mentioned other operations and/or The functions are respectively for realizing the corresponding flow of the method 100 in FIG. 1 , and for the sake of brevity, details are not described here.

Fig. 5 shows a schematic block diagram of an apparatus 400 for image processing according to an embodiment of the present invention. As shown in Figure 5, the device 500 includes:

The obtaining unit 510 is configured to determine a first training filter according to the non-smooth area image block of the enhancement layer image and the non-smooth area image block of the base layer image, so that the first training filter satisfies: according to the first training filter The similarity between the first prediction information determined by the detector and the non-smooth area image block of the base layer image and the first original information determined according to the non-smooth area image block of the enhancement layer image satisfies a first preset condition, wherein, The base layer image corresponds to the enhancement layer image;

A determining unit 520, configured to determine a candidate upsampling filter according to the first training filter, where the candidate upsampling filter includes the first training filter;

For determining a target upsampling filter from candidate upsampling filters, the candidate upsampling filter including the first training filter, and transmitting the target upsampling filter to the decoding unit 530, the candidate upsampling filter The sampling filter includes the first training filter acquired by the acquiring unit 510;

A decoding unit 530, configured to obtain the target upsampling filter from the determining unit 520, and determine prediction information according to the target upsampling filter and the base layer image block;

Decoding the target image block according to the prediction information and the residual information obtained from the target code stream, wherein the target image block is located in the enhancement layer image, and the base layer image block is located in the base layer image , and the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

Optionally, the obtaining unit 510 is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter satisfies: according to The similarity between the second training filter and the second prediction information determined by the smooth area image block of the base layer image and the second original information determined by the smooth area image block of the enhancement layer image satisfies a second preset condition , where the base layer image corresponds to the enhancement layer image; and

The determining unit 520 is further configured to determine a candidate upsampling filter according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter Train the filter.

Optionally, the determining unit 520 is specifically configured to determine the smoothness of the target image according to the feature information of the base layer image block, where the feature information includes coding block label information of the base layer image block or the base layer image block The residual information of the image block;

The target upsampling filter is determined according to the smoothness of the target image block.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The determining unit 520 is specifically configured to acquire first indication information for indicating the target upsampling filter from the target code stream,

It is used for determining the target up-sampling filter according to the first indication information.

Optionally, the alternative upsampling filter also includes a conventional filter, and

The determining unit 520 is specifically configured to determine the texture degree of the target image block;

It is used for determining the target up-sampling filter according to the texture degree of the target image block.

According to the device for image processing in the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and no transmission filter is required The coefficients and indexes can improve the coding performance and improve the effect and performance of image processing.

The device 400 for image processing according to the embodiment of the present invention may correspond to the encoding end in the method of the embodiment of the present invention, and each unit in the device 400 for image processing is the module and the above-mentioned other operations and/or The functions are respectively for realizing the corresponding flow of the method 200 in FIG. 3 , and for the sake of brevity, details are not repeated here.

Fig. 6 shows a schematic block diagram of an encoder 500 for image processing according to an embodiment of the present invention. As shown in Figure 6, the decoder 500 includes:

bus 510;

a processor 520 connected to the bus;

A memory 530 connected to the bus;

Wherein, the processor 520 invokes the program stored in the memory 530 through the bus 510, so as to determine the first training filter according to the non-smooth region image blocks of the enhancement layer image and the non-smooth region image blocks of the base layer image, to Make the first training filter satisfy: the first prediction information determined according to the first training filter and the non-smooth area image block of the base layer image and the first primitive determined according to the non-smooth area image block of the enhancement layer image The similarity between information satisfies a first preset condition, wherein the base layer image corresponds to the enhancement layer image;

determining an alternative upsampling filter based on the first training filter, wherein the candidate upsampling filter includes the first training filter;

From the candidate upsampling filters, a target upsampling filter is determined;

determining prediction information based on the target upsampling filter and the base layer image block;

According to the prediction information, the target image block is encoded to generate a target code stream, wherein the target image block is located in the enhancement layer image, the base layer image block is located in the base layer image, and the basic image block is in the The spatial position in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image

Optionally, the processing unit 520 is further configured to determine a second training filter according to the smooth region image block of the enhancement layer image and the smooth region image block of the base layer image, so that the second training filter satisfies: according to The similarity between the second training filter and the second prediction information determined by the smooth area image block of the base layer image and the second original information determined by the smooth area image block of the enhancement layer image satisfies a second preset condition , where the base layer image corresponds to the enhancement layer image;

It is used for determining a candidate upsampling filter according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

Optionally, the processing unit 520 is specifically configured to determine the smoothness of the target image according to feature information of the base layer image block, where the feature information includes coded block label information of the base layer image block or The residual information of the image block;

The target upsampling filter is determined according to the smoothness of the target image block.

Optionally, the processing unit 520 is specifically configured to determine a candidate upsampling filter according to the first training filter, the second training filter, and the traditional filter, where the candidate upsampling filter includes the first training filter a training filter, the second training filter and the legacy filter;

is used to perform encoding processing on the target image block according to the prediction information to generate a target code stream, where the target code stream includes first indication information used to indicate the target upsampling filter, and the first indication information is used in Decoding the encoded target image block is used as a basis for obtaining the target upsampling filter.

Optionally, the processing unit 520 is specifically configured to determine a candidate upsampling filter according to the first training filter and the traditional filter, where the candidate upsampling filter includes the first training filter and the traditional filter. filter;

Used to determine the texture degree of the target image block;

It is used for determining the target up-sampling filter according to the texture degree of the target image block.

For the encoder for image processing according to the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and there is no need for The filter coefficients and indexes are transmitted, so that the encoding performance can be improved, and the effect and performance of image processing can be improved.

The encoder 500 for image processing according to the embodiment of the present invention may correspond to the encoding end in the method of the embodiment of the present invention, and each unit or module in the encoder 500 for image processing and the above-mentioned other operations and The/or functions are respectively for realizing the corresponding flow of the method 100 in FIG. 1 , and for the sake of brevity, details are not repeated here.

Fig. 7 shows a schematic block diagram of a decoder 600 for image processing according to an embodiment of the present invention. As shown in Figure 7, the decoder 600 includes:

bus 610;

a processor 620 connected to the bus;

A memory 630 connected to the bus;

Wherein, the processor 620 calls the program stored in the memory 630 through the bus 610, so as to determine the first training filter according to the non-smooth region image blocks of the enhancement layer image and the non-smooth region image blocks of the base layer image , so that the first training filter satisfies: the first prediction information determined according to the first training filter and the non-smooth region image block of the base layer image and the first prediction information determined according to the non-smooth region image block of the enhancement layer image A similarity between original information satisfies a first preset condition, wherein the base layer image corresponds to the enhancement layer image;

determining an alternative upsampling filter based on the first training filter, wherein the candidate upsampling filter includes the first training filter;

determining a target upsampling filter from among candidate upsampling filters, the candidate upsampling filter comprising the first training filter;

determining prediction information based on the target upsampling filter and the base layer image block;

According to the prediction information and the residual information obtained from the target code stream, the target code stream is decoded to obtain the target image block, wherein the target image block is located in the enhancement layer image, and the base layer image block is It is located in the base layer image, and the spatial position of the basic image block in the base layer image corresponds to the spatial position of the target image block in the enhancement layer image.

Optionally, the processing unit 620 is further configured to determine a second training filter according to the smooth area image block of the enhancement layer image and the smooth area image block of the base layer image, so that the second training filter satisfies: according to The similarity between the second training filter and the second prediction information determined by the smooth area image block of the base layer image and the second original information determined by the smooth area image block of the enhancement layer image satisfies a second preset condition , where the base layer image corresponds to the enhancement layer image; and

It is used for determining a candidate upsampling filter according to the first training filter and the second training filter, wherein the candidate upsampling filter includes the first training filter and the second training filter.

Optionally, the processing unit 620 is specifically configured to determine the smoothness of the target image according to feature information of the base layer image block, where the feature information includes coded block label information of the base layer image block or The residual information of the image block;

The target upsampling filter is determined according to the smoothness of the target image block.

Optionally, the processing unit 620 is specifically configured to determine a candidate upsampling filter according to the first training filter, the second training filter and the traditional filter, where the candidate upsampling filter includes the first training filter a training filter, the second training filter and the legacy filter;

The method is used for acquiring first indication information for indicating the target up-sampling filter from the target code stream, and determining the target up-sampling filter according to the first indication information. .

Optionally, the processing unit 620 is specifically configured to determine a candidate upsampling filter according to the first training filter and the traditional filter, where the candidate upsampling filter includes the first training filter and the traditional filter. filter;

Used to determine the texture degree of the target image block;

The target upsampling filter is determined according to the texture degree of the target image block.

According to the image processing decoder of the embodiment of the present invention, by determining the upsampling filter according to the smooth area and the non-smooth area, the number of upsampling filters can be reduced while improving the effect of upsampling and there is no need to transmit filter coefficients And indexing, so as to improve the coding performance and improve the effect and performance of image processing.

The decoder 600 for image processing according to the embodiment of the present invention may correspond to the decoding end in the method of the embodiment of the present invention, and each unit in the decoder 600 for image processing is a module and the above-mentioned other operations and The/or functions are respectively for realizing the corresponding flow of the method 200 in FIG. 3 , and for the sake of brevity, details are not described here again.

It should be noted that, in order to make the target upsampling filter used by the encoding end and the decoding end (encoder, decoder) consistent, it is required that the encoding end and the decoding end select the target upsampling filter in the same way. In other words, the decoding end processing method may be determined according to the described encoding end processing method, or the encoding end processing method may be determined according to the described decoding end processing method.

It should be understood that the term "and/or" in this article is only an association relationship describing associated objects, which means that there may be three relationships, for example, A and/or B may mean: A exists alone, and A and B exist at the same time , there are three cases of B alone. In addition, the character "/" in this article generally indicates that the contextual objects are an "or" relationship.

It should be understood that in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of each process should be determined by its functions and internal logic, rather than by the embodiment of the present invention. The implementation process constitutes any limitation.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present invention.

Those skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.

If the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, and other media that can store program codes. .

The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (20)

1. a kind of method for image procossing is it is characterised in that methods described includes：

Non-smooth areas image block according to enhancement layer image and the non-smooth areas image block of basic tomographic image, determine the first instruction Practice wave filter, so that described first training wave filter meets：According to the described first training wave filter and described basic tomographic image The first information of forecasting that non-smooth areas image block determines is determined with the non-smooth areas image block according to described enhancement layer image The first raw information between similarity meet first pre-conditioned, wherein, described basic tomographic image and described enhancement layer Image is corresponding；

According to the described first training wave filter, determine alternative up-sampling filter, wherein, described alternative up-sampling filter includes Described first training wave filter；

From described alternative up-sampling filter, determine target up-sampling filter；

According to described target up-sampling filter and Primary layer image block, determine information of forecasting；

According to described information of forecasting, coded treatment is carried out to target image block, to generate target code stream, wherein, described target figure As block is located in described enhancement layer image, described Primary layer image block is located in described basic tomographic image, and described primary image Locus in described basic tomographic image for block locus phase in described enhancement layer image with described target image block Corresponding.

2. method according to claim 1 is it is characterised in that methods described also includes：

Smooth region image block according to described enhancement layer image and the smooth region image block of described basic tomographic image, determine Two training wave filters, so that described second training wave filter meets：According to the described second training wave filter and described Primary layer figure The second information of forecasting that the smooth region image block of picture determines is determined with the smooth region image block according to described enhancement layer image The second raw information between similarity meet second pre-conditioned, wherein, described basic tomographic image and described enhancement layer Image is corresponding；And

Described according to described first training wave filter, determine alternative up-sampling filter, further include：

According to the described first training wave filter and described second training wave filter, determine alternative up-sampling filter, wherein, described Alternative up-sampling filter includes described first training wave filter and described second training wave filter.

3. method according to claim 2 it is characterised in that described from described alternative up-sampling filter, determine mesh Put on sampling filter, including：

According to the characteristic information of described Primary layer image block, determine the smoothness of described target image, wherein, described characteristic information Encoding block label information including described Primary layer image block or the residual information to described Primary layer image block；

According to the smoothness of described target image block, determine described target up-sampling filter.

4. method according to claim 2 is it is characterised in that train according to the described first training wave filter and described second Wave filter, determines alternative up-sampling filter, further includes：

According to the described first training wave filter, described second training wave filter and conventional filter, determine alternative up-sampling filtering Device, wherein, described alternative up-sampling filter includes described first training wave filter, described second training wave filter and described biography System wave filter；And

Described coded treatment is carried out to described target image block according to described information of forecasting, to generate target code stream, including：

According to described information of forecasting, coded treatment is carried out to described target image block, to generate target code stream, described target code stream Including the first configured information for indicating described target up-sampling filter, described first configured information is in order to above-mentioned in decoding As the foundation obtaining described target up-sampling filter during target image block after coding.

5. method according to claim 1, it is characterised in that described train wave filter according to described first, determines alternative Up-sampling filter, further includes：

According to the described first training wave filter and conventional filter, determine alternative up-sampling filter, wherein, described alternative on adopt Sample wave filter includes described first training wave filter and described conventional filter；And

Described determination target up-sampling filter, including：

Determine the texture of described target image block；

According to the texture of described target image block, determine described target up-sampling filter.

6. a kind of method for image procossing is it is characterised in that methods described includes：

Non-smooth areas image block according to enhancement layer image and the non-smooth areas image block of basic tomographic image, determine the first instruction Practice wave filter, so that described first training wave filter meets：According to the described first training wave filter and described basic tomographic image The first information of forecasting that non-smooth areas image block determines is determined with the non-smooth areas image block according to described enhancement layer image The first raw information between similarity meet first pre-conditioned, wherein, described basic tomographic image and described enhancement layer Image is corresponding；

According to the described first training wave filter, determine alternative up-sampling filter, wherein, described alternative up-sampling filter includes Described first training wave filter；

From described alternative up-sampling filter, determine target up-sampling filter, described alternative up-sampling filter includes institute State the first training wave filter；

According to described target up-sampling filter and Primary layer image block, determine information of forecasting；

The residual information obtaining according to described information of forecasting and from target code stream, carries out decoding process to described object code stream, To obtain described target image block, wherein, described target image block is located in described enhancement layer image, described Primary layer image block In described basic tomographic image, and locus in described basic tomographic image for the described primary image block and described target figure As locus in described enhancement layer image for the block is corresponding.

7. method according to claim 6 is it is characterised in that methods described also includes：

Smooth region image block according to described enhancement layer image and the smooth region image block of described basic tomographic image, determine Two training wave filters, so that described second training wave filter meets：According to the described second training wave filter and described Primary layer figure The second information of forecasting that the smooth region image block of picture determines is determined with the smooth region image block according to described enhancement layer image The second raw information between similarity meet second pre-conditioned, wherein, described basic tomographic image and described enhancement layer figure As corresponding；And described according to described first training wave filter, determine alternative up-sampling filter, further include：

According to the described first training wave filter and described second training wave filter, determine alternative up-sampling filter, wherein, described Alternative up-sampling filter includes described first training wave filter and described second training wave filter.

8. method according to claim 7 it is characterised in that described from described alternative up-sampling filter, determine mesh Put on sampling filter, including：

According to the characteristic information of described Primary layer image block, determine the smoothness of described target image, wherein, described characteristic information Encoding block label information including described Primary layer image block or the residual information to described Primary layer image block；

According to the smoothness of described target image block, determine described target up-sampling filter.

9. method according to claim 8 is it is characterised in that train according to the described first training wave filter and described second Wave filter, determines alternative up-sampling filter, further includes：

According to the described first training wave filter, described second training wave filter and conventional filter, determine alternative up-sampling filtering Device, wherein, described alternative up-sampling filter includes described first training wave filter, described second training wave filter and described biography System wave filter；And

Described determine target up-sampling filter from described alternative up-sampling filter, including：

From described target code stream, obtain the first configured information for indicating described target up-sampling filter,

According to described first configured information, determine described target up-sampling filter.

10. method according to claim 6, it is characterised in that described train wave filter according to described first, determines alternative Up-sampling filter, further includes：

According to the described first training wave filter and conventional filter, determine alternative up-sampling filter, wherein, described alternative on adopt Sample wave filter includes described first training wave filter and described conventional filter；And

Described determination target up-sampling filter, including：

Determine the texture of described target image block；

According to the texture of described target image block, determine described target up-sampling filter.

A kind of 11. devices for image procossing are it is characterised in that described device includes：

Acquiring unit, for the non-smooth areas image of the non-smooth areas image block according to enhancement layer image and basic tomographic image Block, determines the first training wave filter, so that described first training wave filter meets：According to the described first training wave filter and described The first information of forecasting that the non-smooth areas image block of basic tomographic image determines and the non-smooth area according to described enhancement layer image Similarity between the first raw information that area image block determines meet first pre-conditioned, wherein, described basic tomographic image with Described enhancement layer image is corresponding；

Determining unit, according to the described first training wave filter, determines alternative up-sampling filter, wherein, described alternative up-sampling Wave filter includes described first training wave filter；

For, from described alternative up-sampling filter, determining target up-sampling filter；

Coding unit, for obtaining described up-sampling filter from described determining unit, and according to described target up-sampling filtering Device and Primary layer image block, determine information of forecasting；

For according to described information of forecasting, coded treatment being carried out to target image block, to generate target code stream, wherein, described mesh Logo image block is located in described enhancement layer image, and described Primary layer image block is located in described basic tomographic image, and described basic Locus in described basic tomographic image for the image block and space bit in described enhancement layer image for the described target image block Put corresponding.

12. devices according to claim 11 are it is characterised in that described acquiring unit is additionally operable to according to described enhancement layer figure The smooth region image block of picture and the smooth region image block of described basic tomographic image, determine the second training wave filter, so that institute State the second training wave filter to meet：True according to the smooth region image block of the described second training wave filter and described basic tomographic image Between the second fixed information of forecasting and the second raw information according to the smooth region image block determination of described enhancement layer image Similarity satisfaction second is pre-conditioned, and wherein, described basic tomographic image is corresponding with described enhancement layer image；And

Described determining unit is further used for, according to the described first training wave filter and described second training wave filter, determining alternative Up-sampling filter, wherein, described alternative up-sampling filter includes described first training wave filter and described second training filter Ripple device.

13. devices according to claim 12 are it is characterised in that described determining unit is specifically for according to described Primary layer The characteristic information of image block, determines the smoothness of described target image, and wherein, described characteristic information includes described basic tomographic image The encoding block label information of block or the residual information to described Primary layer image block；

For the smoothness according to described target image block, determine described target up-sampling filter.

14. devices according to claim 12 are it is characterised in that described determining unit is further used for according to described first Training wave filter, described second training wave filter and conventional filter, determine alternative up-sampling filter, wherein, described alternative Up-sampling filter includes described first training wave filter, described second training wave filter and described conventional filter；And

Described coding unit specifically for according to described information of forecasting, coded treatment being carried out to described target image block, with generate Target code stream, described target code stream includes the first configured information for indicating described target up-sampling filter, and described first Configured information in order to decode above-mentioned coding after target image block when as obtain described target up-sampling filter foundation.

15. devices according to claim 11 are it is characterised in that described determining unit is further used for according to described first Training wave filter and conventional filter, determine alternative up-sampling filter, and wherein, described alternative up-sampling filter includes described First training wave filter and described conventional filter；

Specifically for determining the texture of described target image block；

For the texture according to described target image block, determine described target up-sampling filter.

A kind of 16. devices for image procossing are it is characterised in that described device includes：

Acquiring unit, for the non-smooth areas image of the non-smooth areas image block according to enhancement layer image and basic tomographic image Block, determines the first training wave filter, so that described first training wave filter meets：According to the described first training wave filter and described The first information of forecasting that the non-smooth areas image block of basic tomographic image determines and the non-smooth area according to described enhancement layer image Similarity between the first raw information that area image block determines meet first pre-conditioned, wherein, described basic tomographic image Corresponding with described enhancement layer image；

Determining unit, for according to the described first training wave filter, determining alternative up-sampling filter, wherein, described alternative on Sampling filter includes described first training wave filter；

For from alternative up-sampling filter, determining target up-sampling filter, described alternative up-sampling filter includes institute State the first training wave filter；

Decoding unit, for obtaining described target up-sampling filter from described determining unit, and up-samples according to described target Wave filter and Primary layer image block, determine information of forecasting；

For according to described information of forecasting and from target code stream obtain residual information, described object code stream is decoded locate Reason, to obtain described target image block, wherein, described target image block is located in described enhancement layer image, described Primary layer figure As block is located in described basic tomographic image, and locus in described basic tomographic image for the described primary image block and described mesh Locus in described enhancement layer image for the logo image block is corresponding.

17. devices according to claim 16 are it is characterised in that described acquiring unit is additionally operable to according to described enhancement layer figure The smooth region image block of picture and the smooth region image block of described basic tomographic image, determine the second training wave filter, so that institute State the second training wave filter to meet：True according to the smooth region image block of the described second training wave filter and described basic tomographic image Between the second fixed information of forecasting and the second raw information according to the smooth region image block determination of described enhancement layer image Similarity satisfaction second is pre-conditioned, and wherein, described basic tomographic image is corresponding with described enhancement layer image；And

Described determining unit is further used for, according to the described first training wave filter and described second training wave filter, determining alternative Up-sampling filter, wherein, described alternative up-sampling filter includes described first training wave filter and described second training filter Ripple device.

18. devices according to claim 17 are it is characterised in that described determining unit is specifically for according to described Primary layer The characteristic information of image block, determines the smoothness of described target image, and wherein, described characteristic information includes described basic tomographic image The encoding block label information of block or the residual information to described Primary layer image block；

According to the smoothness of described target image block, determine described target up-sampling filter.

19. devices according to claim 17 are it is characterised in that described determining unit is further used for according to described first Training wave filter, described second training wave filter and conventional filter, determine alternative up-sampling filter, wherein, described alternative Up-sampling filter includes described first training wave filter, described second training wave filter and described conventional filter；

For from described target code stream, obtaining the first configured information for indicating described target up-sampling filter,

For according to described first configured information, determining described target up-sampling filter.

20. devices according to claim 16 are it is characterised in that described determining unit is further used for according to described first Training wave filter and conventional filter, determine alternative up-sampling filter, and wherein, described alternative up-sampling filter includes described First training wave filter and described conventional filter；

For determining the texture of described target image block；

For the texture according to described target image block, determine described target up-sampling filter.