CN104052933A - Method for judging dynamic range mode and image acquisition device thereof - Google Patents

Abstract

The invention provides a method for determining a dynamic range mode and an image acquisition device thereof. The method comprises the following steps. A source image is acquired. And analyzing the brightness of the source image to determine multiple over-exposed areas and under-exposed areas of the source image. Then, an overexposure estimation value of the overexposed area and an underexposure estimation value of the underexposed area are calculated according to the weight map. And comparing the overexposure estimation value and the underexposure estimation value with one or more threshold values to determine a dynamic range mode suitable for the image capturing device.

Description

Method for judging dynamic range mode and image acquisition device thereof

technical field

The invention relates to a method for determining a dynamic range mode and an image acquisition device thereof.

Background technique

The so-called "dynamic range" refers to the range or ratio between the maximum brightness value and the minimum brightness value in the picture. For photography, the dynamic range can be divided into "the dynamic range of the camera" and "the dynamic range of the scene". Among them, the dynamic range of the camera refers to the range in which the photosensitive element can accept brightness changes. The dynamic range of a scene refers to the range of brightness differences in the shooting scene, that is, the difference between the brightest area and the darkest area in the picture.

When the dynamic range of the scene is greater than the dynamic range of the camera, it means that there are extreme bright and dark parts in the shooting scene, which exceed the color gradation that the photosensitive element can record, so there will be completely black or completely white areas in the photo. For example, shooting portraits and scenery outside the window at the same time indoors, shooting trees under the sun and the shade of trees, etc., due to the huge difference between light and dark in such shooting scenes, the image quality will be significantly reduced.

In order to overcome the above defects, some cameras provide a high dynamic range mode, that is, through image processing technology, the dynamic range of the processed image is greater than that provided by a single image captured by a general camera. However, whether the camera uses the high dynamic range imaging mode must be set by the camera user based on shooting experience. That is to say, the camera user must use human eyes to judge whether the current shooting scene is suitable for shooting in the high dynamic range imaging mode or in the normal mode. However, most users often fail to use the HDR mode correctly to capture better images due to inexperience or wrong judgment.

Contents of the invention

The present invention provides a method for determining a dynamic range mode and an image acquisition device thereof, which can automatically detect changes in a current shooting scene, and then adaptively select and switch a dynamic range (Dynamic Range, DR) mode.

A method for determining a dynamic range mode of the present invention is suitable for an image acquisition device performing video processing. This determination method includes the following steps. Get the source image first. And analyze the brightness and darkness of the source image to determine the overexposure area and underexposure area of the source image. An estimated overexposure value of the overexposed region and an estimated underexposure value of the underexposed region are calculated according to the weighting map. And compare the estimated overexposure value and the estimated underexposure value with one or more critical values, so as to determine the dynamic range mode suitable for the image acquisition device.

In an embodiment of the present invention, the dynamic range modes that the above-mentioned image acquisition device can use include normal dynamic range (Normal DR, NDR) mode, wide dynamic range (Wide DR, WDR) mode, high dynamic range (High DR , HDR) mode and Ultra High Dynamic Range (Ultra High DR, UHDR) mode.

In an embodiment of the present invention, the step of analyzing the brightness and darkness of the source image to determine the overexposed area and the underexposed area includes: dividing the source image into a plurality of blocks; calculating the average brightness of each block; And judge whether each block belongs to an over-exposed area or an under-exposed area according to each brightness average value.

In an embodiment of the present invention, before the step of calculating the estimated overexposure value and the estimated underexposure value, it further includes setting a plurality of weight setting values of the weight map. Wherein, each weight setting value corresponds to each block of the source image respectively.

In an embodiment of the present invention, the step of calculating the estimated overexposure value of the overexposed area and the estimated underexposure value of the underexposed area according to the weight map includes: calculating the weight setting value corresponding to the overexposed area The calculation is performed to obtain an estimated overexposure value; and the weight setting value corresponding to the underexposed area is calculated to obtain an estimated underexposure value.

In an embodiment of the present invention, the above determination method further includes performing face detection on the source image to determine whether there are one or more human face regions in the source image. If yes, increase the weight setting value corresponding to the block to which the face area belongs.

In an embodiment of the present invention, the step of comparing the estimated overexposure value and the estimated underexposure value with at least one critical value to determine a dynamic range mode suitable for the image acquisition device includes: adding the overexposure an estimated value of exposure and an estimated value of underexposure to obtain a sum of the estimated values; and comparing the sum of the estimated values with the first, second and third critical values to determine the dynamic range suitable for use by the image acquisition device model.

In an embodiment of the present invention, the above determination method further includes controlling the image acquisition device to automatically switch to a suitable dynamic range mode.

An image acquisition device of the present invention is suitable for video processing, and includes an image sensor, a memory and a processor. Wherein, the image sensor is used to obtain the source image. The memory is used to store source images and weight maps. The processor is used to analyze the lightness and darkness of the source image to determine the overexposed area and the underexposed area of the source image, and calculate the estimated overexposure value of the overexposed area and the estimated underexposure value of the underexposed area according to the weight map, Then compare the estimated overexposure value and the estimated underexposure value with one or more critical values, so as to determine the dynamic range mode suitable for the image acquisition device.

Based on the above, the method for judging the dynamic range mode and its image acquisition device provided by the present invention can judge the change of the current shooting scene by detecting the light and dark ratio of a source image, and then adaptively select and automatically switch suitable image acquisition devices The dynamic range mode to use.

In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail with reference to the accompanying drawings.

Description of drawings

FIG. 1 is a block diagram of an image acquisition device according to an embodiment of the present invention;

Fig. 2 is a flowchart of a method for determining a dynamic range mode according to an embodiment of the present invention;

Fig. 3 is a schematic diagram of conversion of a dynamic range mode according to an embodiment of the present invention;

Fig. 4 is a flowchart of a method for determining a dynamic range mode according to another embodiment of the present invention;

5A is a schematic diagram showing overexposed areas and underexposed areas according to another embodiment of the present invention;

Fig. 5B is a schematic diagram of a weight map according to another embodiment of the present invention.

Explanation of reference signs:

100: image acquisition device;

110: image sensor;

120: memory;

130: processor;

b1~b25: blocks;

W1～W25: Weight setting value;

N: exposure normal area;

O: overexposed area;

U: underexposed area;

S210-S240: each step of the determination method of the dynamic range mode in an embodiment;

S401-S425: each step of the determination method of the dynamic range mode in another embodiment.

Detailed ways

The image acquisition device provided by the present invention is not only suitable for obtaining a single static image, but also suitable for automatically detecting changes in the current shooting scene when performing video processing (such as video recording), and then adaptively selects and switches the dynamic range (Dynamic Range, DR) mode. Fig. 1 is a block diagram of an image acquisition device according to an embodiment of the present invention. The image acquisition device 100 of this embodiment is, for example, a digital camera, a digital single-eye (Digital Single Lens Reflex, DSLR) camera, a digital video camera (Digital Video Camcorder, DVC), etc., or other smart phones or tablets with image/video acquisition functions Computers and the like are not limited to the above.

Referring to FIG. 1 , the image acquisition device 100 at least includes an image sensor 110 , a memory 120 and a processor 130 . The image sensor 110 includes a lens, a CCD/CMOS photosensitive element, etc., and can be used to acquire images. The memory 120 can be any form of fixed or removable random access memory (Random Access Memory, RAM), read-only memory (Read-Only Memory, ROM), flash memory (Flash memory) or other similar components, and Can be used to store source images and data. The processor 130 performs automatic scene detection (scene detection) according to the source image, and judges the currently suitable dynamic range mode according to the ambient brightness.

Among them, the dynamic range modes that can be used by the image acquisition device 100 of this embodiment include normal dynamic range (Normal DR, NDR) mode, wide dynamic range (Wide DR, WDR) mode, high dynamic range (High DR, HDR) mode And Ultra High Dynamic Range (Ultra High DR, UHDR) mode. Since the dynamic range is the ratio of the maximum brightness value to the minimum brightness value, it has no units. In this embodiment, the NDR mode used by the image acquisition device 100 can record a dynamic range of about 8-9 levels; the WDR mode can record a dynamic range of about 10-11 levels; the HDR mode can record a dynamic range of about 12-13 levels. Range; UHDR mode can record approximately more than 13 levels of dynamic range. The above is only an exemplary embodiment, and the classification method of the dynamic range mode is not limited to the above.

Fig. 2 is a flowchart of a method for determining a dynamic range mode according to an embodiment of the present invention. The method of this embodiment is applicable to the image acquisition device 100 of FIG. 1 , and the detailed steps of the determination method of this embodiment are described below in conjunction with each component in the image acquisition device 100:

In step S210 , the image sensor 110 acquires a source image and stores the source image in the memory 120 . Next, in step S220, the processor 130 analyzes the brightness and darkness of the source image to determine an overexposure area and an underexposure area of the source image.

In step S230, the processor 130 calculates an overexposure estimated value of the overexposed area and an underexposed estimated value of the underexposed area according to the weighting map. For the user, the captured image can usually be divided into foreground and background, and the foreground is often the main part that the user cares about. Therefore, the weight map, for example, gives different weights according to the foreground area and background area of the source image. set value. Then, the weight setting value corresponding to the overexposure area is calculated to obtain an estimated overexposure value. Similarly, the estimated value of underexposure can be obtained by calculating the weight setting value corresponding to the underexposed area.

In step S240 , the processor 130 compares the estimated overexposure value and the estimated underexposure value with one or more critical values, so as to determine the current dynamic range mode suitable for the image capturing device 100 . Wherein, the threshold value can be preset by those skilled in the art according to actual application conditions, and the scope thereof is not limited here. To put it simply, when the processor 130 judges that the estimated overexposure value and the estimated underexposure value are too large, it means that the range of the difference between light and dark in the current shooting scene is too large, which may exceed the color that the photosensitive element of the image sensor 110 can record. order. It is therefore necessary to switch the dynamic range mode used by the image capture device 100 .

Fig. 3 is a schematic diagram showing a conversion of a dynamic range mode according to an embodiment of the present invention. Referring to FIG. 3 , when the dynamic range of the scene is low (that is, the range of difference between light and dark of the shooting scene is small), the NDR mode can be used. When the dynamic range of the scene gradually increases (that is, the range of the difference between light and dark of the shooting scene gradually increases), the dynamic range mode can be gradually adjusted to WDR mode, HDR mode and UHDR mode.

The dynamic range that can be recorded by the photosensitive element of the image sensor 110 is fixed. Therefore, if the dynamic range of the output image is to be increased, an image processing method must be used to achieve it. For example, the WDR mode of this embodiment can acquire a single image, and adjust the gamma curve through the image processing module in the processor 130, that is, by brightening the dark part of the image and darkening the overexposed area before Output the processed image.

However, the post-processing method using a single image can only be adjusted in a limited range. Therefore, if the dynamic range of the scene continues to increase and exceeds the range that WDR mode can handle, HDR mode and UHDR mode should be used instead.

The HDR mode and UHDR mode used in this embodiment, for example, adopt the multiple exposure technology, that is, control the image sensor 110 to shoot the same scene multiple times under different exposures or different apertures, and combine the acquired multiple images into one that takes into account both the bright part and the A single processed image of dark detail. In more detail, the video processing speed of the HDR mode of this embodiment is to capture 60 images (or referred to as frames) per second and output 30 images per second. Wherein, the odd-numbered images are, for example, short-exposure shots, and the even-numbered images are, for example, long-exposure shots. That is to say, interlaced shooting is performed in the manner of short exposure and long exposure, and every two images are synthesized into one output image. The video processing speed of the UHDR mode of this embodiment is to capture 30 images per second and output 30/15 images per second. Interleaved shooting is also carried out in the way of short exposure and long exposure, and every two images are synthesized into one output image. The difference between UHDR mode and HDR mode is that the exposure time of UHDR mode can be increased to 2 times that of HDR mode, so it can have more dark part detail data.

In order to make the content of the present invention clearer, another embodiment is given below as an example of the actual implementation of the present invention.

Fig. 4 is a flowchart of a method for determining a dynamic range mode according to another embodiment of the present invention. Wherein, FIG. 4 is a detailed implementation of the method for determining the dynamic range mode in FIG. 2 .

Please refer to FIG. 4 , firstly, acquire a source image, wherein the size of the source image is P*Q, where P and Q are positive integers (step S401 ). Next, the source image is divided into multiple blocks (step S403). The size of each block is, for example, N*N, where N is a multiple of 2, N<P and N<Q.

Next, the average brightness of each block is calculated (step S405). That is, for each block, the average brightness of all pixels in the block is calculated. Then, it can be judged whether each block belongs to an over-exposed area or an under-exposed area according to each brightness average value (step S407). For example, if the source image is presented in 256 color levels (8 bits), if the average brightness of the block is 251-256, it will be recorded as the overexposure area O; if the average brightness of the block is 1-256 10 is recorded as an underexposed area U. FIG. 5A is a schematic diagram showing overexposed areas and underexposed areas according to another embodiment of the present invention. Please refer to FIG. 5A , assuming that the source image has 25 blocks, which are respectively marked as b1˜b25. Among them, blocks b1, b2, b19, b20, b24, and b25 are marked as "U", which means they are underexposed areas; blocks b3, b4, b7-b9, b12-b13, b16-b17 are marked as "O" , which means it is an over-exposed area; the other blocks marked with "N" are normal-exposed areas.

Step S409, setting multiple weight setting values of the weight map. Wherein, each weight setting value corresponds to each block of the source image respectively. For example, FIG. 5B is a schematic diagram of a weight map according to another embodiment of the present invention. Referring to FIG. 5B , the weight map has a total of 25 weight setting values, which are respectively marked as W1 - W25 . Wherein, the weight setting value W1 is corresponding to the block b1 shown in FIG. 5A, and the value of the weight setting value W1 is set to 1, for example; the weight setting value W2 is corresponding to the block b2 shown in FIG. 5A , the value of the weight setting value W2 is set to 1, for example; and so on. From the weight diagram shown in FIG. 5B , it can be seen that the closer to the center of the image, the higher the weight setting value; conversely, the closer to the image periphery, the lower the weight setting value. This method of setting the weight setting value is because the center of the image is mostly the foreground or the subject area that the user cares about, so the proportion of the weight setting value is increased.

In another embodiment, the method for setting the weight setting value further includes performing face detection on the source image to determine whether there is a face area in the source image. If yes, the weight setting value corresponding to the block to which the face area belongs may be increased additionally.

It should be noted that the weight map is not limited to the form shown in FIG. 5B , it can also be stored in a table or other forms and stored in the memory of the image acquisition device (such as the memory 120 in FIG. 1 ), and corresponds to Different shooting scenes may have weight maps in various forms, so those skilled in the art can select a suitable weight map according to the actual shooting scene.

After the setting of the weight map is completed, step S411 can be continued to calculate the estimated overexposure value of the overexposed area and the estimated underexposure value of the underexposed area according to the weight map. The weight setting value corresponding to the overexposed area is calculated to obtain an estimated overexposure value; and the weight setting value corresponding to the underexposed area is calculated to obtain an estimated underexposure value. In one embodiment, the weight setting values corresponding to the overexposed areas can be added to obtain an overexposed estimated value; and the weighted settings corresponding to the underexposed areas can be added to obtain an underexposed estimated value value. Taking FIG. 5A and FIG. 5B as an example for illustration, the estimated value of overexposure is 17, and the estimated value of underexposure is 7. A sum of estimated values can be obtained by adding the estimated overexposure value and the estimated underexposure value.

In step S413, it is determined whether the sum of estimated values is between the first threshold TH1 and the second threshold TH2. If yes, the operation mode suitable for the image capture device is the WDR mode (step S415 ). If not, continue to step S417.

In step S417, it is determined whether the sum of estimated values is between the second threshold TH2 and the third threshold TH3. If yes, the operating mode suitable for the image capturing device is the HDR mode (step S419 ). If not, continue to step S421.

Step S421, judging whether the sum of estimated values is greater than a third threshold TH3. If yes, the operation mode suitable for the image capture device is the UHDR mode (step S423 ). If not, continue to step S425, and the operation mode suitable for the image acquisition device is the NDR mode. The setting of the above-mentioned first, second and third critical values TH1, TH2 and TH3 will vary with the value of the weight setting value, so it can be set by those skilled in the art according to the actual application situation. No limitation is imposed here.

It should be noted that when the image acquisition device performs real-time video processing, it is still suitable to use the method flow shown in FIG. 2 or FIG. 4 for detection and judgment. Because the present invention uses only one source image for detection, it can determine the suitable dynamic range mode, which has the advantages of low complexity and fast calculation speed, and thus meets the time requirement of real-time performance. In addition, although the present invention can detect and determine the dynamic range mode for each frame in the video, in one embodiment, the image acquisition device can be set, for example, when consecutive M (M is a positive integer) frames are Switching is performed after judging that the dynamic range modes are the same. In this way, it is possible to prevent the switching of the dynamic range mode from being too frequent and affecting the processing efficiency of the image acquisition device.

To sum up, when the image acquisition device provided by the present invention is performing video processing, it can judge the dynamic range change of the current shooting scene by detecting the ratio of light and dark of a source image, and then adaptively select and automatically switch suitable for image acquisition. The dynamic range mode used by the device. Accordingly, the user can save the trouble and trouble of judging the change of the shooting scene by human eyes and manually adjusting the dynamic range mode. In addition, the determination method of the dynamic range mode provided by the present invention has the advantages of low complexity and fast calculation speed, thus meeting the real-time requirements of video processing.

Although the present invention has cited the above examples, it is not intended to limit the present invention. Anyone with ordinary knowledge in the technical field may make some changes and modifications without departing from the spirit and scope of the present invention. , so the protection scope of the present invention should be as defined by the following claims.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the various embodiments of the present invention. scope.

Claims (10)

1. a decision method for dynamic range pattern, is applicable to carry out an image acquiring device of a Video processing, it is characterized in that, this decision method comprises:

Obtain one and carry out source images;

Analyze the bright dark degree that this carrys out source images, to determine that this comes multiple overexposures region and the region of underexposure of source images;

Calculate an overexposure estimated value in those overexposure regions and a under-exposed estimated value of those region of underexposure according to a weight map; And

This overexposure estimated value and this under-exposure estimated value and at least one critical value are compared, and judgement is according to this suitable for the dynamic range pattern that this image acquiring device uses.

2. decision method according to claim 1, is characterized in that, this dynamic range pattern that this image acquiring device can use comprises normal dynamic range mode, wide dynamic range mode, high dynamic range mode and extreme dynamic range pattern.

3. decision method according to claim 1, is characterized in that, analyzes this and come the bright dark degree of source images, comprises with the step that determines those overexposure regions and region of underexposure:

Cutting apart this, to carry out source images be multiple blocks;

Calculate respectively a respectively average brightness of this block; And

Foundation respectively this average brightness judges respectively respectively whether this block belongs to this overexposure region or this region of underexposure.

4. decision method according to claim 3, is characterized in that, before calculating the step of this overexposure estimated value and this under-exposure estimated value, also comprises:

Set multiple weight setting values of this weight map, wherein respectively this weight setting value corresponds to respectively this and comes respectively this block of source images.

5. decision method according to claim 4, is characterized in that, the step of calculating this overexposure estimated value in those overexposure regions and this under-exposure estimated value of those region of underexposure according to this weight map comprises:

Corresponding those overexposure regions those weight setting values are carried out to computing to obtain this overexposure estimated value, and corresponding those region of underexposure those weight setting values are carried out to computing to obtain this under-exposure estimated value.

6. decision method according to claim 4, is characterized in that, also comprises:

To this come source images carry out one face detect, to judge that this carrys out source images and whether has at least one human face region; And

If so, improve affiliated this weight setting value corresponding to block of this human face region.

7. decision method according to claim 1, is characterized in that, this overexposure estimated value and this under-exposure estimated value and this at least one critical value are compared, and the step that judgement is according to this suitable for this dynamic range pattern that this image acquiring device uses comprises:

Be added this overexposure estimated value and this under-exposure estimated value, to obtain an estimated value summation; And

This estimated value summation and one first, second and third critical value are compared, and judgement is according to this suitable for this dynamic range pattern that this image acquiring device uses.

8. decision method according to claim 1, is characterized in that, after judgement is suitable for the step of this dynamic range pattern of this image acquiring device use, also comprises:

Control this image acquiring device and automatically switch to this dynamic range pattern that is applicable to use.

9. an image acquiring device, is suitable for carrying out a Video processing, it is characterized in that, comprising:

One imageing sensor, obtains one and carrys out source images;

One memory, stores this and comes source images and a weight map;

One processor, analyze the bright dark degree that this carrys out source images, to determine that this comes multiple overexposures region and the region of underexposure of source images, and calculate an overexposure estimated value in those overexposure regions and a under-exposed estimated value of those region of underexposure according to this weight map, this overexposure estimated value and this under-exposure estimated value and at least one critical value are compared, and judgement is according to this suitable for the dynamic range pattern that this image acquiring device uses.

10. image acquiring device according to claim 9, is characterized in that,

The operator scheme of this image acquiring device comprises normal dynamic range mode, wide dynamic range mode, high dynamic range mode and extreme dynamic range pattern.