CN106127698A - Image noise reduction treating method and apparatus - Google Patents

Abstract

The present invention relates to an image noise reduction processing method and device, the method comprising: receiving a photographing instruction; continuously photographing according to the photographing instruction to obtain multiple frames of original images; obtaining ambient brightness values and/or ISO values corresponding to the photographing environment; Judging whether at least one of the following conditions is met: the ambient brightness value is less than or equal to a brightness preset value; the ISO value is greater than or equal to an ISO preset value; A noisy original image; acquiring RAW data of the original image to be denoised, converting the RAW data into YUV data, and performing multi-frame noise reduction processing on the YUV data to obtain an output image. By using this method, clear image quality can be obtained without manual adjustment of exposure time or brightness gain in automatic shooting mode.

Description

Image noise reduction processing method and device

technical field

The present invention relates to the technical field of image processing, in particular to an image noise reduction processing method and device.

Background technique

With the development of technology, digital cameras have spread, and mobile terminals such as smartphones and tablet PCs also have shooting functions. In the fully automatic shooting mode, in order to meet the brightness requirements of the picture in a low-light environment, long exposure or high brightness gain is usually used to achieve it. The long exposure method can make the picture pure, but as the exposure time increases, if there is a slight shake when taking pictures, the picture will be blurred. The way of high brightness gain will be accompanied by serious noise, which makes the picture have obvious graininess. How to obtain a clear image without manually adjusting the exposure time or brightness gain has become a technical problem that needs to be solved at present.

Contents of the invention

Based on this, it is necessary to address the above technical problems and provide an image noise reduction processing method and device that can obtain clear image quality without manual adjustment of exposure time or brightness gain in automatic shooting mode.

An image noise reduction processing method, the method comprising:

Receive camera instructions;

Continuous shooting according to the photographing instruction to obtain multiple frames of original images;

Obtain the ambient brightness value and/or ISO value corresponding to the shooting environment;

Determine whether at least one of the following conditions is met:

The ambient brightness value is less than or equal to a preset brightness value;

The ISO value is greater than or equal to the ISO preset value;

If so, the original image to be denoised is obtained according to the ambient brightness value or the ISO value;

Acquiring RAW data of the original image to be denoised, converting the RAW data into YUV data, performing multi-frame denoising processing on the YUV data to obtain an output image.

In one of the embodiments, before the step of obtaining the original image to be denoised according to the ambient brightness value or the ISO value, it also includes:

Acquiring a color guide table, the color guide table including the corresponding relationship between the ambient brightness value, the ISO value and the number of original images to be denoised;

The number of corresponding original images to be noise-reduced is determined according to the ambient brightness value or ISO value corresponding to the shooting environment.

In one of the embodiments, the original image to be denoised includes the base image to be denoised and other original images to be denoised; the step of obtaining the original image to be denoised according to the ambient brightness value or ISO value include:

Obtain the focus value of multiple frames of original images;

Select the original image with the largest focus value, and determine the original image with the largest focus value as the base image to be denoised;

Acquire other original images to be denoised from multiple frames of original images according to the number of original images to be denoised corresponding to the ambient brightness value or ISO value.

In one of the embodiments, the step of converting the RAW data into YUV data and performing multi-frame noise reduction processing on the YUV data to obtain the output image step includes:

Converting the RAW data of the original image to be denoised into corresponding YUV data;

Split the YUV data corresponding to the original image to be denoised into a brightness signal and a color signal;

Perform multi-frame noise reduction processing on the luminance signal and color signal corresponding to the original image to be denoised in multiple frames, to obtain a denoised luminance signal and a denoised color signal;

Synthesizing the noise-reduced luminance signal and the noise-reduced color signal into a YUV image;

The synthesized YUV image is subjected to spatial frequency noise reduction processing to obtain an output image.

In one of the embodiments, after the step of performing multi-frame noise reduction processing on the YUV data to obtain the output image, it also includes:

When the output image is displayed, detect the user's touch operation on the display screen;

Obtain the pressure value and pressing time corresponding to the touch operation;

If the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressing preset time, multiple frames of output images are acquired, and the multiple frames of output images are continuously played and displayed.

An image noise reduction processing device, the device comprising:

A receiving module, configured to receive a camera instruction;

A photographing module, configured to continuously photograph according to the photographing instruction to obtain multiple frames of original images;

An acquisition module, configured to acquire the ambient brightness value and/or ISO value corresponding to the shooting environment;

A judging module, configured to judge whether at least one of the following conditions is met: the ambient brightness value is less than or equal to a brightness preset value; the ISO value is greater than or equal to an ISO preset value;

The acquisition module is also used to obtain the noise reduction signal to be reduced according to the ambient brightness value or the ISO value if the ambient brightness value is less than or equal to the brightness preset value, and/or the ISO value is greater than or equal to the ISO preset value. the original image; obtain the RAW data of the original image to be denoised;

The noise reduction module is used to convert the RAW data into YUV data, and perform multi-frame noise reduction processing on the YUV data to obtain an output image.

In one of the embodiments, the obtaining module is also used to obtain the color guide table, which includes the corresponding relationship between the ambient brightness value, the ISO value and the number of original images to be denoised; according to the The ambient brightness value or ISO value corresponding to the shooting environment determines the corresponding number of original images to be denoised.

In one of the embodiments, the original image to be denoised includes the base image to be denoised and other original images to be denoised; the acquisition module is also used to acquire focus values of multiple frames of original images; select the focus value The largest original image, the original image with the largest focus value is determined as the base image to be denoised; according to the number of original images to be denoised corresponding to the ambient brightness value or ISO value, other The original image to be denoised.

In one of the embodiments, the noise reduction module is also used to convert the RAW data of the original image to be denoised into corresponding YUV data; split the YUV data corresponding to the original image to be denoised into luminance signals and the color signal; the luminance signal and the color signal corresponding to the original image to be denoised in multiple frames are respectively subjected to multi-frame denoising processing to obtain the luminance signal after denoising and the color signal after denoising; The luminance signal and the noise-reduced color signal are synthesized into a YUV image; the synthesized YUV image is subjected to spatial frequency noise reduction processing to obtain an output image.

In one of the embodiments, the device also includes:

The detection module is used to detect the user's touch operation on the display screen when the output image is displayed;

The acquisition module is also used to acquire the pressure value and pressing time corresponding to the touch operation;

The display module is used to acquire multiple frames of output images if the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressure preset time, and continuously play and display the multiple frames of output images.

The above image noise reduction processing method and device, after receiving the photographing instruction, continuously photographs according to the photographing instruction to obtain multiple frames of original images. When the brightness corresponding to the shooting environment is less than or equal to the preset brightness value, and/or the ISO value corresponding to the shooting environment is greater than or equal to the ISO preset value, it means that shooting is currently taking place in a low-light high-gain environment. According to the ambient brightness value or ISO value corresponding to the shooting environment, the original image to be denoised is obtained, the RAW data of the original image to be denoised is converted into YUV data, and the YUV data is subjected to multi-frame noise reduction processing to obtain an output image. Due to the multi-frame noise reduction processing of the original image captured in a low-light and high-gain environment, clear and high-quality images can be obtained without manually adjusting the exposure time or brightness gain in the automatic shooting mode.

Description of drawings

Fig. 1 is a flow chart of image noise reduction processing method in one embodiment;

Fig. 2 is the image taken under the long exposure mode in an embodiment;

Fig. 3 is the image taken under the high brightness gain mode in an embodiment;

Fig. 4-1 is the denoising effect diagram of the original image containing grayscale noise in an embodiment;

Figure 4-2 is a partial enlarged view of Figure 4-1 after noise reduction processing;

Fig. 5-1 is the denoising effect diagram of the original image containing color noise in an embodiment;

Figure 5-2 is a partial enlarged view of Figure 5-1 after noise reduction processing;

Fig. 6 is a schematic diagram of performing multi-frame noise reduction with different ISO values in an embodiment;

Fig. 7 is a schematic diagram of an internal structure of a terminal in an embodiment;

Fig. 8 is a schematic structural diagram of an image noise reduction processing device in an embodiment;

Fig. 9 is a schematic structural diagram of an image noise reduction processing device in another embodiment.

detailed description

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

In one embodiment, as shown in FIG. 1 , an image noise reduction processing method is provided, and the method is applied to a terminal with a camera function as an example for illustration, specifically including:

Step 102, receiving a photographing instruction.

Step 104: Continuously shoot according to the camera instruction to obtain multiple frames of original images.

Terminals include digital cameras, smartphones, tablets, etc. The terminal receives a photographing instruction input by the user. The terminal continuously photographs the object to be photographed according to the photographing instruction to obtain multiple frames of original images. When the terminal performs continuous shooting, it does not need to lengthen the exposure time, nor does it need to manually adjust the brightness gain. Continuous shooting can be performed after receiving the camera instruction.

Step 106, acquiring the ambient brightness value and/or ISO value corresponding to the shooting environment.

Step 108, judging whether at least one of the following conditions is met: the ambient brightness value is less than or equal to the brightness preset value; the ISO value is greater than or equal to the ISO preset value; if so, then perform step 110, otherwise, perform step 109, from multiple frames Select a frame of the original image from the original image for noise reduction processing to obtain an output image.

When shooting with a terminal, the corresponding brightness, brightness gain, and exposure time of the environment will have a greater impact on image quality. Among them, the brightness gain can be adjusted by adjusting the ISO (sensitivity) value. The terminal acquires the ambient brightness value and/or ISO value corresponding to the shooting environment. Wherein, the ambient brightness value refers to the ambient brightness value when the terminal previews the object to be photographed. The ISO value refers to the ISO value when the terminal previews the subject. In low-light environment, the image quality can be improved by increasing the exposure time, but the user experience is not good and if there is shaking when taking pictures, the picture will be blurred, as shown in Figure 2. A faster shutter speed can be obtained by increasing the ISO value, but after increasing the ISO value, the image quality is lost and the graininess is obvious, as shown in Figure 3.

If the ambient brightness value corresponding to the shooting environment is less than or equal to the preset brightness value, it means that the terminal is shooting in a low-light environment. If the ISO value corresponding to the shooting environment is greater than or equal to the ISO preset value, it means that the terminal is shooting in a low light and high brightness gain environment. If the ambient brightness value corresponding to the shooting environment is less than or equal to the brightness preset value and the ISO value corresponding to the shooting environment is greater than or equal to the ISO preset value, it means that the terminal is shooting in a low light high brightness gain environment. For example, the preset value of brightness is 100lux, and the default value of ISO is 320, etc., indicating that the terminal is shooting in an environment with low light and high brightness gain.

If the ambient brightness value is greater than the brightness preset value, and/or the ISO value is smaller than the ISO preset value, the terminal acquires a frame of original image in the ZSL (ZeroSecond Later, zero-second delay shooting) queue. Specifically, the terminal may select a frame of original image with the largest focus value in the ZSL queue, that is, select the clearest frame of original image for noise reduction processing. The noise reduction processing method can be processed by a traditional noise reduction method to obtain an output image.

Step 110, acquire the original image to be denoised according to the ambient brightness value or ISO value.

When it is determined that the terminal is shooting in a low-light high-gain environment, the terminal acquires the original image to be noise-reduced from multiple frames of original images according to the ambient brightness value or ISO value corresponding to the shooting environment. The original image to be denoised may be all original images obtained by continuous shooting by the terminal, or may be part of the original images.

The ambient brightness values corresponding to the shooting environment are different, and the number of original images to be noise-reduced acquired by the terminal is different. The ISO value corresponding to the shooting environment is different, and the number of original images to be denoised acquired by the terminal is also different.

Step 112, acquiring RAW data of the original image to be denoised, converting the RAW data into YUV data, and performing multi-frame denoising processing on the YUV data to obtain an output image.

The original image to be denoised includes a base image to be denoised and other original images to be denoised. The terminal obtains one of the original images to be denoised as a base image to be denoised, and performs multi-frame denoising processing with other original images to be denoised.

Specifically, the terminal obtains the RAW data of the original image to be denoised (including the base image to be denoised and other original images to be denoised), performs basic processing on the original image to be denoised, and converts each frame of the image to be denoised The RAW data of the original image is converted to corresponding YUV (a color encoding method) data. RAW (raw) data is all the data of the original image recorded by the photosensitive element of the terminal. Basic processing includes dark current correction, vignetting compensation, demosaicing, gamma correction, color restoration and Bayer (an image processing method) noise reduction processing, etc.

In the traditional way, in the fully automatic shooting mode, Bayer noise reduction processing will be performed on the original image, and then noise reduction processing in the YUV spatial frequency domain will be performed to obtain the output image. For images captured in low-light and high-brightness gain environments, although this processing method can quickly remove grayscale noise and high-frequency color noise generated under high-brightness gain, low-frequency color noise is still obvious. As shown in Figure 4-1, it is the denoising rendering of a frame of original image containing grayscale noise. The partially enlarged picture is shown in Figure 4-2. After the noise reduction process, the details of the picture are lost, resulting in the picture showing an oil painting feeling. As shown in Figure 5-1, it is the denoising rendering of a frame of original image containing color noise. The partially enlarged picture is shown in Figure 5-2. After the noise reduction process, the high-frequency noise is effectively eliminated, but the low-frequency noise is still obvious, resulting in color overflow and saturation reduction in the picture.

In this embodiment, after the terminal converts the RAW data of multiple frames of the original image to be denoised into corresponding YUV data, it performs multi-frame denoising processing on the YUV data.

In one of the embodiments, converting the RAW data into YUV data, performing multi-frame noise reduction processing on the YUV data, and obtaining an output image includes: converting the RAW data of the original image to be denoised into corresponding YUV data; The YUV data corresponding to the noisy original image is split into luminance signal and color signal; the luminance signal and color signal corresponding to the multi-frame original image to be denoised are subjected to multi-frame noise reduction processing, and the denoised luminance signal and the denoised signal are obtained. The noised color signal; the noise-reduced luminance signal and the noise-reduced color signal are synthesized into a YUV image; the synthesized YUV image is subjected to spatial frequency noise reduction processing to obtain an output image.

The terminal converts the RAW data of each frame of the original image to be denoised into corresponding YUV data. YUV data can be in YUV420 format or YUV422 format. YUV data includes luminance signals and color signals. When YUV data adopts YUV420 format, every four luminance signals share a set of color signals; when YUV data adopts YUV422 format, every two luminance signals share a set of color signals.

The terminal splits the YUV data corresponding to each frame of the original image to be denoised into a brightness signal and a color signal. The terminal performs multi-frame noise reduction processing on the multiple brightness signals and the multiple color signals respectively. Specifically, the terminal may first perform multi-frame noise reduction processing on multiple brightness signals to obtain noise-reduced brightness signals, and then perform multi-frame noise reduction processing on multiple color signals to obtain noise-reduced color signals. The terminal may first perform multi-frame noise reduction processing on multiple color signals to obtain noise-reduced color signals, and then perform multi-frame noise reduction processing on multiple brightness signals to obtain noise-reduced brightness signals. In order to further improve processing efficiency, the terminal may also simultaneously perform multi-frame noise reduction processing on multiple luminance signals and multi-frame noise reduction processing on multiple color signals.

The terminal uses the noise-reduced luminance signal and the noise-reduced color information to synthesize an image in YUV format (YUV image for short). The synthesized YUV image can be in YUV420 format or YUV422 format, etc. The terminal performs spatial frequency noise reduction processing on the synthesized YUV image to obtain an output image. The output image can be an image in JPG format. The output image is output through the display screen and displayed to the user.

In this embodiment, after receiving the photographing instruction, continuous photographing is performed according to the photographing instruction to obtain multiple frames of original images. When the brightness corresponding to the shooting environment is less than or equal to the preset brightness value, and/or the ISO value corresponding to the shooting environment is greater than or equal to the ISO preset value, it means that shooting is currently taking place in a low-light high-gain environment. According to the ambient brightness value or ISO value corresponding to the shooting environment, the original image to be denoised is obtained, the RAW data of the original image to be denoised is converted into YUV data, and the YUV data is subjected to multi-frame noise reduction processing to obtain an output image. Due to the multi-frame noise reduction processing of the original image captured in a low-light and high-gain environment, clear and high-quality images can be obtained without manually adjusting the exposure time or brightness gain in the automatic shooting mode.

In one embodiment, the method further includes: detecting the user's touch operation on the display screen; obtaining the pressing time corresponding to the touch operation, and judging whether the pressing time exceeds a preset time; if so, entering into rapid continuous shooting according to the touch operation mode, continuously shooting multiple frames of original images in the fast continuous shooting mode, performing noise reduction processing on multiple frames of original images, and outputting multiple frames of noise-reduced images.

In this embodiment, if the terminal detects that the pressing time of the user touching the display screen exceeds the preset time, the terminal enters the rapid continuous shooting mode. In the fast continuous shooting mode, the terminal performs continuous and fast shooting to capture multiple frames of original images. For example, in the fast continuous shooting mode, 20 frames of raw images can be continuously captured. The terminal performs noise reduction processing on each frame of the original image continuously captured. Specifically, the terminal performs Bayer noise reduction processing and YUV noise reduction processing in the spatial frequency domain on each frame of the original image continuously captured to obtain a noise-reduced image. The image after noise reduction can be in JPG format. This provides convenience for the user to perform the continuous shooting mode.

In one embodiment, before the step of obtaining the original image to be noise-reduced according to the ambient brightness value or the ISO value, it also includes: obtaining a color guide table, which includes the ambient brightness value, the ISO value, and the original image to be noise-reduced The corresponding relationship between the numbers; determine the corresponding number of original images to be denoised according to the ambient brightness value or the ISO value.

The number of original images to be denoised and the parameter settings of the denoising engine required for multi-frame denoising under different exposure conditions are different. If the number of denoised images is too large, the speed of multi-frame denoising processing will be slowed down. The parameters in the noise reduction engine can be set to different strengths, the higher the strength of the parameters, the better the noise reduction effect. Therefore, when performing multi-frame denoising, it is necessary to select an appropriate number of original images to be denoised and the corresponding parameter strength of the denoising engine.

In this embodiment, a color guide table is stored in the terminal. The color guide table includes the correspondence between multiple parameters such as the ambient brightness value, ISO value, the number of original images to be noise-reduced, the signal-to-noise ratio, the standard deviation before multi-frame noise reduction, and the standard deviation after multi-frame noise reduction. relationship, as shown in Table 1. Among them, the standard deviation before multi-frame noise reduction refers to the standard deviation of the original image after only basic noise reduction processing, and the standard deviation is equivalent to the degree of noise. The standard deviation after multi-frame noise reduction is lower than that before multi-frame noise reduction. It can be seen that after multi-frame noise reduction processing, the noise is suppressed and the image quality becomes clearer.

Table I:

According to Table 1, when the ambient brightness is higher than 100lux and the ISO value is lower than 320, the signal-to-noise ratio is close to 30dB, and the image quality is relatively clear. At this time, multi-frame noise reduction processing is unnecessary. When the ambient brightness is between 75lux and 100lux, and the ISO value is between 320 and 400, the signal-to-noise ratio will drop by about 2dB to 3dB, which will make people feel that the image quality will change significantly, so it is necessary to start multi-frame Noise reduction processing. Therefore, a more reasonable brightness preset value and ISO preset value can be set according to the data in the color guide table.

The ambient brightness and ISO value are segmented through the color guide table. As the ambient brightness decreases and the ISO value increases, the resolution gradually decreases, and the number of original images to be noise-reduced that require multi-frame noise reduction processing will increase. After the terminal obtains the ambient brightness value and ISO value corresponding to the shooting environment, it compares the ambient brightness value or ISO value with the color guide table, and quickly determines the paragraphs that fall into the color guide table according to the ambient brightness value or ISO value. The number of raw images to denoise required for multi-frame denoising.

In one embodiment, the original image to be denoised includes a base image to be denoised and other original images to be denoised; the step of obtaining the original image to be denoised according to the ambient brightness value or the ISO value includes: acquiring multiple frames of the original image The focus value; select the original image with the largest focus value, and determine the original image with the largest focus value as the base image to be denoised; according to the number of original images to be denoised corresponding to the ambient brightness value or ISO value in multiple frames of original images Obtain other original images to be denoised.

In this embodiment, after acquiring the ambient brightness value and/or ISO value corresponding to the shooting environment, the terminal quickly determines the number of original images to be noise-reduced according to the data in the color guide table. The original image to be denoised includes a base image to be denoised and other original images to be denoised.

The terminal acquires multiple frames of original images taken in the ZSL queue. The terminal obtains the focus value of the original image, and selects a frame of original image with the largest focus value as the base image to be denoised, that is, selects the clearest frame of original image as the base image to be denoised. According to the number of original images to be denoised, other original images to be denoised are obtained from multiple frames of original images. Specifically, the terminal acquires other original images to be denoised after the base image to be denoised according to the number of original images to be denoised according to the shooting sequence. The terminal also obtains the focus values of all original images in the ZSL queue, sorts the focus values of all original images, and obtains other noise-reducing base images according to the focus value corresponding to the base image to be de-noised and the number of original images to be de-noised. The original image. Since other original images to be denoised are obtained in descending order of focus values, an image with clearer quality can be obtained after multi-frame denoising processing.

Multi-frame noise reduction means that after the basic noise reduction processing of multiple frames of the original image to be denoised, the processed base image to be denoised is used as the base, and is superimposed with other processed original images to be denoised to remove noise. For example, the number of original images to be denoised is 2 frames, the noise at a certain pixel in the processed base image to be denoised is 5dB, and the noise at this pixel of other processed original images to be denoised is - 5dB, then the noise at this pixel after the two frames of original images are superimposed is 0, thus effectively eliminating the noise at this pixel.

The terminal acquires RAW data of the base image to be denoised and other original images to be denoised, and converts the RAW data into corresponding YUV data. And the YUV data corresponding to the base image to be denoised is split into luminance signal and color information, and the YUV data corresponding to other original images to be denoised are split into luminance signal and color signal. The terminal performs multi-frame noise reduction processing on the luminance signal corresponding to the base image to be denoised and the luminance signals corresponding to other original images to be denoised, to obtain a denoised luminance signal. The terminal performs multi-frame noise reduction processing on the color signal corresponding to the base image to be denoised and the color signals corresponding to other original images to be denoised, to obtain a denoised color signal. The terminal synthesizes the noise-reduced luminance signal and the noise-reduced color signal into a frame of YUV format image (referred to as YUV image), and performs spatial frequency noise reduction processing on the synthesized YUV image, thus obtaining clear picture quality output image.

For different exposure intensities, it is necessary to select different numbers of original images to be denoised according to the data in the color guide table. As the ambient brightness value decreases and the ISO value increases, in order to obtain a clear picture quality, the number of original images to be denoised also needs to increase accordingly. As shown in Figure 6, when the ISO value is 800, the number of original images to be denoised is 2; when the ISO value is 1250, the number of original images to be denoised is 3; when the ISO value is 2000, the number of original images to be denoised is The number of original images to be denoised is 4; when the ISO value is 2500, the number of original images to be denoised is 5; when the ISO value is 3200, the number of original images to be denoised is 6.

In one embodiment, after the step of performing multi-frame noise reduction processing on the YUV data to obtain the output image, it also includes: when the output image is displayed, detecting the user's touch operation on the display screen; obtaining the pressure corresponding to the touch operation value and pressing time; if the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressing preset time, multiple frames of output images are acquired, and the multiple frames of output images are continuously played and displayed.

In this embodiment, the user can touch the display screen with fingers. The display screen may be an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch screen, or an LCD (Liquid Crystal Display, liquid crystal display) touch screen, or a pressure screen (also called a pressure-sensing screen), etc.

Touch actions can include taps, hard presses, and long presses. The pressure value and pressing time can be respectively used as two dimensions for identifying touch operations. Specifically, it can be determined by comparing the pressure value (represented by x) with the pressure preset value (represented by X), and the comparison of the pressing time (represented by t) and the time preset value (represented by T). to identify. As shown in Table 2 below:

Table II:

Pressure value x<X x>X x≤X pressing time t<T t<T t≥T touch operation click press hard Press

As shown in Table 1, when x<X and t<T, the touch operation is recognized as a click, and the icon of the application program or the virtual button can be triggered by clicking. When x≥X and t<T, the touch operation is recognized as a hard press, and the shortcut operation panel can be displayed by pressing hard, and the application can be started or switched by triggering the control corresponding to the application in the shortcut operation panel , or switch pages within the app. When x<X and t≥T, the touch operation is recognized as a long press. When the output image is displayed, all the output images under the folder currently displayed on the screen can be obtained by long pressing, and the output images under this folder will be played and displayed continuously.

In this embodiment, when the output image is displayed, by detecting the user’s touch operation on the display screen, if the pressure value corresponding to the touch operation is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressing preset time, then it can be Continuously play multiple frames of output images for display. In this way, the user can conveniently and quickly check multiple frames of clear output images without the need for the user to click one by one, which provides convenience for the user.

As shown in FIG. 7 , it is a schematic diagram of an internal structure of a terminal in an embodiment. The terminal includes a processor connected through a system bus, a non-volatile storage medium, an internal memory, a network interface, a display screen, a photographing device and an input device. Wherein, the non-volatile storage medium of the terminal stores an operating system, and also includes an image noise reduction processing device, and the image noise reduction processing device is used to implement an image noise reduction processing method. The processor is used to provide computing and control capabilities to support the operation of the entire terminal. The internal memory in the terminal provides an environment for the operation of the image noise reduction processing device in the non-volatile storage medium. Computer-readable instructions can be stored in the internal memory. When the computer-readable instructions are executed by the processor, the processing The processor performs an image noise reduction processing method. The network interface is used for network communication with the server, such as sending and uploading the output image to the server for sharing. The display screen of the terminal may be a liquid crystal display screen or an electronic ink display screen, etc., and the input device may be a touch layer covered on the display screen.

In one embodiment, as shown in FIG. 8 , an image noise reduction processing device is provided, including: a receiving module 802, a shooting module 804, an acquisition module 806, a judging module 808, and a noise reduction module 810, wherein:

The receiving module 802 is configured to receive a photographing instruction.

The photographing module 804 is configured to continuously photograph according to the photographing instruction to obtain multiple frames of original images.

An acquisition module 806, configured to acquire an ambient brightness value and/or an ISO value corresponding to the shooting environment.

The judging module 808 is configured to judge whether at least one of the following conditions is satisfied: the ambient brightness value is less than or equal to the brightness preset value; the ISO value is greater than or equal to the ISO preset value.

The obtaining module 802 is also used to obtain the original image to be noise-reduced according to the ambient brightness value or the ISO value if the ambient brightness value is less than or equal to the brightness preset value, and/or the ISO value is greater than or equal to the ISO preset value; Noisy raw image RAW data.

The noise reduction module 810 is configured to convert the RAW data into YUV data, and perform multi-frame noise reduction processing on the YUV data to obtain an output image.

In one embodiment, the obtaining module 806 is also used to obtain the color guide table, which includes the corresponding relationship between the ambient brightness value, the ISO value, and the number of original images to be noise-reduced; according to the corresponding ambient brightness of the shooting environment value or ISO value determines the corresponding amount of original image to be denoised.

In one embodiment, the original image to be denoised includes the base image to be denoised and other original images to be denoised; the acquisition module 806 is also used to acquire the focus values of multiple frames of original images; select the original image with the largest focus value , determining the original image with the largest focus value as the base image to be denoised; obtaining other original images to be denoised in multiple frames of original images according to the number of original images to be denoised corresponding to the ambient brightness value or ISO value.

In one embodiment, the noise reduction module 810 is also used to convert the RAW data of the original image to be denoised into corresponding YUV data; split the YUV data corresponding to the original image to be denoised into brightness signals and color signals; The luminance signal and color signal corresponding to the multi-frame original image to be denoised are subjected to multi-frame denoising processing to obtain the denoised luminance signal and the denoised color signal; the denoised luminance signal and the denoised The color signal is synthesized into a YUV image; the synthesized YUV image is subjected to spatial frequency noise reduction processing to obtain an output image.

In one embodiment, as shown in FIG. 9, the device further includes: a detection module 812 and a display module 814, wherein:

The detection module 812 is configured to detect the user's touch operation on the display screen when the output image is displayed.

The obtaining module is also used to obtain the pressure value and pressing time corresponding to the touch operation.

The presentation module 814 is configured to acquire multiple frames of output images and continuously play and display the multiple frames of output images if the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressing preset time.

The above examples only express several implementations of the present invention, and the description thereof is relatively specific and detailed, but should not be construed as limiting the patent scope of the present invention. It should be pointed out that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention should be based on the appended claims.

Claims (10)

1. An image noise reduction processing method, said method comprising: Receive camera instructions; Continuous shooting according to the photographing instruction to obtain multiple frames of original images; Obtain the ambient brightness value and/or ISO value corresponding to the shooting environment; Determine whether at least one of the following conditions is met: The ambient brightness value is less than or equal to a preset brightness value; The ISO value is greater than or equal to the ISO preset value; If so, the original image to be denoised is obtained according to the ambient brightness value or the ISO value; Acquiring RAW data of the original image to be denoised, converting the RAW data into YUV data, performing multi-frame denoising processing on the YUV data to obtain an output image. 2. The method according to claim 1, wherein, before the step of obtaining the original image to be denoised according to the ambient brightness value or the ISO value, further comprising: Acquiring a color guide table, the color guide table including the corresponding relationship between the ambient brightness value, the ISO value and the number of original images to be denoised; The number of corresponding original images to be noise-reduced is determined according to the ambient brightness value or ISO value corresponding to the shooting environment. 3. The method according to claim 2, wherein the original image to be denoised comprises a base image to be denoised and other original images to be denoised; The steps of obtaining the original image to be denoised include: Obtain the focus value of multiple frames of original images; Select the original image with the largest focus value, and determine the original image with the largest focus value as the base image to be denoised; Acquire other original images to be denoised from multiple frames of original images according to the number of original images to be denoised corresponding to the ambient brightness value or ISO value. 4. The method according to claim 1, wherein the described RAW data is converted into YUV data, and the YUV data is subjected to multi-frame noise reduction processing to obtain an output image step comprising: Converting the RAW data of the original image to be denoised into corresponding YUV data; Split the YUV data corresponding to the original image to be denoised into a brightness signal and a color signal; Perform multi-frame noise reduction processing on the luminance signal and color signal corresponding to the original image to be denoised in multiple frames, to obtain a denoised luminance signal and a denoised color signal; Synthesizing the noise-reduced luminance signal and the noise-reduced color signal into a YUV image; The synthesized YUV image is subjected to spatial frequency noise reduction processing to obtain an output image. 5. method according to claim 1, is characterized in that, after described YUV data is carried out multi-frame denoising process, obtains the step of output image, also comprises: When the output image is displayed, detect the user's touch operation on the display screen; Obtain the pressure value and pressing time corresponding to the touch operation; If the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressing preset time, multiple frames of output images are acquired, and the multiple frames of output images are continuously played and displayed. 6. An image noise reduction processing device, characterized in that the device comprises: A receiving module, configured to receive a camera instruction; A photographing module, configured to continuously photograph according to the photographing instruction to obtain multiple frames of original images; An acquisition module, configured to acquire the ambient brightness value and/or ISO value corresponding to the shooting environment; A judging module, configured to judge whether at least one of the following conditions is met: the ambient brightness value is less than or equal to a brightness preset value; the ISO value is greater than or equal to an ISO preset value; The acquisition module is also used to obtain the noise reduction signal to be reduced according to the ambient brightness value or the ISO value if the ambient brightness value is less than or equal to the brightness preset value, and/or the ISO value is greater than or equal to the ISO preset value. the original image; obtain the RAW data of the original image to be denoised; The noise reduction module is used to convert the RAW data into YUV data, and perform multi-frame noise reduction processing on the YUV data to obtain an output image. 7. The device according to claim 6, wherein the obtaining module is further used to obtain a color guide table, which includes an ambient brightness value, an ISO value, and the number of original images to be denoised. Correspondence among them; determine the corresponding number of original images to be noise-reduced according to the ambient brightness value or ISO value corresponding to the shooting environment. 8. The device according to claim 7, wherein the original image to be denoised comprises a base image to be denoised and other original images to be denoised; the acquisition module is also used to acquire multiple frames of original The focus value of the image; select the original image with the largest focus value, and determine the original image with the largest focus value as the base image to be denoised; the number of original images to be denoised corresponding to the ambient brightness value or ISO value Obtain other original images to be denoised in multiple frames of original images. 9. The device according to claim 6, wherein the noise reduction module is also used for converting the RAW data of the original image to be denoised into corresponding YUV data; corresponding to the original image to be denoised The YUV data of YUV is split into luminance signal and color signal; the luminance signal and color signal corresponding to the multi-frame original image to be denoised are subjected to multi-frame noise reduction processing respectively, and the denoised luminance signal and the denoised color signal are obtained ; Synthesizing the noise-reduced luminance signal and the noise-reduced color signal into a YUV image; performing spatial frequency noise reduction processing on the synthesized YUV image to obtain an output image. 10. The device according to claim 6, further comprising: The detection module is used to detect the user's touch operation on the display screen when the output image is displayed; The acquisition module is also used to acquire the pressure value and pressing time corresponding to the touch operation; The display module is used to acquire multiple frames of output images if the pressure value is less than or equal to the pressure preset value and the pressing time is greater than or equal to the pressure preset time, and continuously play and display the multiple frames of output images.