WO2020135234A1

WO2020135234A1 - Image processing method and apparatus

Info

Publication number: WO2020135234A1
Application number: PCT/CN2019/126786
Authority: WO
Inventors: 沈海杰; 徐爱臣
Original assignee: 青岛海信电器股份有限公司
Priority date: 2018-12-25
Filing date: 2019-12-19
Publication date: 2020-07-02
Also published as: CN109686342B; CN109686342A

Abstract

Provided are an image processing method and apparatus, the method comprises: calculating the gray average pixel brightness of an image to be processed, and the respective component average pixel brightness on the R channel, G channel and B channel of the image to be processed (101); according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel and B channel, determining the key color channel of the image to be processed (102); according to the component average pixel brightness of the image to be processed on the key color channel, determining the target brightness adjustment curve (103); and using the target brightness adjustment curve to adjust the brightness of the image to be processed (104). By applying this method, the contrast of the image display can be enhanced based on the key color scene of the image, and the viewing experience of the user can be improved.

Description

Image processing method and device

This disclosure requires the priority of a Chinese patent application filed on December 25, 2018 in the Chinese Patent Office with the application number 201811593713.8 and the invention titled "An Image Processing Method and Device", the entire contents of which are incorporated by reference in this disclosure .

Technical field

The present disclosure relates to the field of image processing technology, and in particular, to an image processing method and device.

Background technique

At present, backlight control technology for display devices is gradually emerging. Through the backlight control technology, not only can power be saved, but also the contrast of the display device to the image display can be improved.

The image in RGB color mode includes three color channels: R channel (red channel), G channel (green channel), and B channel (blue channel). How to enhance the contrast of the image display based on the key color scene of the image and improve the user's viewing experience is a problem that needs to be solved at present.

Summary of the invention

The present disclosure provides an image processing method and device. By applying this method, the contrast of the image display can be enhanced based on the key color scene of the image, and the viewing experience of the user can be improved.

According to an aspect of an exemplary embodiment, an image processing method is provided, including: calculating a gray average pixel brightness of an image to be processed, and components of the image to be processed on the R channel, the G channel, and the B channel, respectively Average pixel brightness; determine the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R, G, and B channels; according to the image to be processed in the The component average pixel brightness on the key color channel determines a target brightness adjustment curve; the target brightness adjustment curve is used to adjust the brightness of the image to be processed.

In some exemplary embodiments, the determining the key color channel of the image to be processed according to the grayscale average pixel brightness and the component average pixel brightness on the R channel, G channel, and B channel includes: : Calculate the proportion of the brightness distribution of the image to be processed on the R channel, G channel and B channel according to the average pixel brightness of the R channel, G channel and B channel; And in the B channel, the color channel whose brightness distribution ratio is greater than the ratio threshold and the component average pixel brightness is greater than the gray average pixel brightness is determined as the key color channel of the image to be processed.

In some exemplary embodiments, the determining the target brightness adjustment curve according to the component average pixel brightness of the image to be processed on the key color channel includes: based on a low brightness brightness threshold corresponding to the key color channel , A mid-brightness threshold and a high-brightness threshold to determine the brightness interval to which the component average pixel brightness on the key color channel belongs; a brightness adjustment curve corresponding to the brightness interval to which the component average pixel brightness on the key color channel belongs To determine the target brightness adjustment curve.

In some exemplary embodiments, the use of the target brightness adjustment curve to perform brightness adjustment on the image to be processed includes: determining a key processing area in the image to be processed based on the key color channel; The target brightness adjustment curve adjusts the brightness of at least one pixel in the critical processing area.

In some exemplary embodiments, the determining the key processing area in the image to be processed based on the key color channel includes: separately counting the gray of the image to be processed on the R channel, the G channel, and the B channel Degree distribution histogram, the grayscale distribution histogram is used to represent the number of pixels in the grayscale color channel in each grayscale interval in the image to be processed; according to the R channel, G channel and B The gray distribution histogram on the channel determines the color channel with the largest number of pixels on each gray scale interval; the gray scale interval that meets the following conditions is determined as the target gray scale interval: the color channel with the largest number of pixels is the Key color channel; in the image to be processed, an area composed of pixels on the key color channel whose gray level is within the target gray scale interval is determined as a key processing area.

According to an aspect of an exemplary embodiment, a display device is provided, including: a processor, a memory, and a display; the memory is connected to the processor and configured to store computer instructions; the processor, and the The memory is connected to the display and is configured to execute the computer instructions to cause the display device to perform the above method.

According to an aspect of the exemplary embodiments, there is provided a computer-readable non-volatile storage medium having computer instructions stored thereon, the computer instructions implementing the above method when executed by a processor.

BRIEF DESCRIPTION

1 is a flowchart of an embodiment of an image processing method provided by an exemplary embodiment in the present disclosure;

Figure 2 is a schematic diagram of a low-brightness brightness adjustment curve, a medium-brightness brightness adjustment curve, and a high-brightness brightness adjustment curve;

FIG. 3 is an example of the histogram of the gray distribution of the image to be processed on the R channel;

4 is an example of the histogram of the gray distribution of the image to be processed on the G channel;

FIG. 5 is an example of the histogram of the gray distribution of the image to be processed on the B channel;

FIG. 6 is an example of the grayscale distribution map of the pixels in the image to be processed on each color channel;

FIG. 7 is an example of the grayscale brightness adjustment curve;

8 is a hardware structure diagram of a display device provided by an exemplary embodiment in the present disclosure;

9 is a block diagram of an embodiment of a display device provided by an exemplary embodiment in the present disclosure.

detailed description

Exemplary embodiments will be described in detail here, examples of which are shown in the drawings. When referring to the drawings below, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

The terminology used in the present disclosure is for the purpose of describing specific embodiments only, and is not intended to limit the present disclosure. The singular forms "a", "said" and "the" used in this disclosure and the appended claims are also intended to include the majority forms unless the context clearly indicates other meanings. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more associated listed items.

It should be understood that although the terms first, second, third, etc. may be used to describe various information in this disclosure, the information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present disclosure, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "when" or "in response to a determination".

Please refer to FIG. 1, which is a flowchart of an embodiment of an image processing method according to an exemplary embodiment of the present disclosure. The method may be applied to a display device, such as a smart TV, and includes the following steps:

Step 101: Calculate the gray average pixel brightness of the image to be processed, and the component average pixel brightness of the image to be processed on the R channel, the G channel, and the B channel, respectively.

In the embodiments of the present disclosure, for convenience of description, the average pixel brightness of pixels in the grayscale image of the image to be processed is referred to as grayscale average pixel brightness, and is referred to as APL _Gray . The specific process of calculating the gray average pixel brightness APL _Gray can adopt any relevant scheme, which will not be described in detail in this disclosure.

In the embodiment of the present disclosure, the average pixel brightness of the image to be processed on the R channel, the G channel, and the B channel can also be calculated separately. For convenience of description, the average pixel brightness is referred to as component average pixel brightness, and the component average pixel brightness on the R channel of the image to be processed is recorded as APL _R , and the component average pixel brightness on the G channel is recorded as APL _G , in The average pixel brightness of the component on the B channel is recorded as APL _B.

Taking the component average pixel brightness APL _R on the R channel of the image to be processed as an example, the calculation process includes: adding the brightness of each pixel on the R channel on the image to be processed, and then dividing by the total number of pixels, ie The above APL _R can be derived.

For the specific processes of the above APL _G and APL _B , refer to the process of calculating the APL _R described above, which will not be described in detail in this disclosure.

Step 102: Determine the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel, and B channel.

Among them, the key color channel of the image to be processed is one of the R channel, the G channel, and the B channel.

In an embodiment of the present disclosure, according to the average pixel brightness of the R channel, G channel, and B channel calculated in step 101 above, the respective images on the R channel, G channel, and B channel of the image to be processed can be calculated. Proportion of brightness distribution. Among them, for the convenience of description, the proportion of the brightness distribution of the image to be processed on the R channel is denoted as R _p , the proportion of the brightness distribution of the image to be processed on the G channel is denoted as G _p , and the proportion of the image to be processed on the B channel The proportion of the brightness distribution is recorded as B _p .

Specifically, the above R _p , G _p , and B _p can be calculated by the following formula (1), formula (2), and formula (3), respectively:

In the embodiment of the present disclosure, in the R channel, the G channel, and the B channel, the brightness distribution ratio is greater than a preset ratio threshold (the ratio threshold, for example, 33%), and the component average pixel brightness is greater than the grayscale average pixel brightness The color channel of APL _Gray is determined as the key color channel of the image to be processed.

Step 103: Determine the target brightness adjustment curve according to the component average pixel brightness of the image to be processed on the key color channel.

In an embodiment of the present disclosure, the corresponding low brightness brightness threshold, medium brightness brightness threshold, and high brightness brightness threshold may be set for any color channel among the R channel, the G channel, and the B channel. For convenience of description, the R channel corresponding to low luminance brightness threshold value is referred to as Th _RL, the brighter the luminance threshold referred to as Th _RM, highlight luminance threshold referred to as Th _RH; the G channel corresponding to low luminance brightness threshold value is referred to as Th _GL, The mid-brightness threshold is denoted as Th _GM , the high-brightness threshold is denoted as Th _GH ; the low-brightness threshold corresponding to channel B is denoted as Th _BL , the medium-brightness threshold is denoted as Th _BM , and the high-brightness threshold is denoted as Th _BH .

In the embodiment of the present disclosure, the corresponding low-brightness brightness adjustment curve, medium-brightness brightness adjustment curve, and high-brightness brightness adjustment curve can also be set for any color channel among the R channel, the G channel, and the B channel. For example, as shown in FIG. 2, it is a schematic diagram of a low-brightness brightness adjustment curve, a medium-brightness brightness adjustment curve, and a high-brightness brightness adjustment curve. Among them, the solid line is the highlight brightness adjustment curve (marked as H in the figure), the dashed line is the medium brightness brightness adjustment curve (marked as M in the figure), and the dot-dash line is the low brightness brightness adjustment curve (marked as L in the figure).

Subsequently, taking the R channel as an example, the corresponding low-brightness threshold Th _RL , medium-brightness threshold Th _RM , and high-brightness threshold Th _RH divide the 0-255 brightness range into four brightness intervals, respectively: (0, Th _{RL )} , (Th _RL , Th _{RM )} , (Th _RM , Th _{RH )} , (Th _RH , 255), and each brightness interval corresponds to a brightness adjustment curve.

Among them, (0, Th _RL) This brightness interval belongs to a low brightness brightness interval, and its corresponding brightness adjustment curve can be a low brightness brightness adjustment curve; (Th _RH , 255) this brightness interval belongs to a high brightness brightness interval, which The corresponding brightness adjustment curve can be a highlight brightness adjustment curve.

The two brightness intervals (Th _RL , Th _RM) and (Th _RM , Th _RH ) belong to the mid-brightness interval. The brightness adjustment curves corresponding to the two mid-brightness intervals are different. Among them, (Th _RL , Th _RM) The brightness adjustment curve corresponding to this brightness interval can be obtained by weighting the aforementioned low-brightness brightness adjustment curve and the preset mid-brightness brightness adjustment curve, (Th _RM , Th _RH) the brightness adjustment curve corresponding to this brightness interval can be preset The mid-brightness brightness adjustment curve is weighted with the above high-brightness brightness adjustment curve.

Specifically, (Th _RL , Th _RM) the brightness adjustment curve corresponding to this brightness interval can be expressed by the following formula (4); (Th _RM , Th _RH) the brightness adjustment curve corresponding to this brightness interval can be expressed by the following formula (5) said.

M _L = (1-α)*L+α*M………………………………[4]

M _H = (1-β)*M+β*H………………………………[5]

In the above formula (4), M _L represents the brightness adjustment curve corresponding to the brightness interval of (Th _RL , Th _{RM )} , L represents the above low brightness brightness adjustment curve, M represents the above mid brightness brightness adjustment curve, and α is a weighting coefficient , Which is a decimal greater than 0 and less than 1.

In the above formula (5), M _H represents the brightness adjustment curve corresponding to the brightness interval of (Th _RM , Th _{RH )} , H represents the above-mentioned highlight brightness adjustment curve, β is the weighting coefficient, which is greater than 0 and less than 1. Decimal.

Based on the above description, in the embodiment of the present disclosure, the brightness interval to which the average pixel brightness of the component of the image to be processed on the key color channel belongs can be determined, and the brightness adjustment curve corresponding to the brightness interval is determined as the target brightness adjustment curve.

Step 104: Use the target brightness adjustment curve to adjust the brightness of the image to be processed.

In the embodiment of the present disclosure, for the key color channel determined in the above step 102, the gray scale interval where the pixel points are distributed on the key color channel may be determined, and then, based on the determined gray scale interval, to be processed Identify key processing areas in the image.

Subsequently, the brightness of any pixel in the key processing area can be adjusted using the target brightness adjustment curve determined in step 103 above.

The above-mentioned specific process of determining the gray-scale interval of pixels distributed on the key color channel, and determining the key processing area in the image to be processed based on the determined gray-scale interval may include:

First of all, the histogram of the gray distribution of the to-be-processed image on the R channel, G channel and B channel is calculated. For example, as shown in FIG. 3, it is an example of the gray distribution histogram of the image to be processed on the R channel, and as shown in FIG. 4, it is a kind of gray distribution histogram of the image to be processed on the G channel. The example, as shown in FIG. 5, is an example of the histogram of the gray distribution of the image to be processed on the B channel.

Taking the gray distribution histogram shown in FIG. 3 as an example, the horizontal axis represents the gray scale interval. For example, the gray scale range of 0-255 is divided into 32 gray scale intervals, and 0-8 is a gray scale. Interval, 9-17 is a grayscale interval, 18-26 is a grayscale interval, and so on, until the grayscale interval of 247-255; the vertical axis represents the grayscale on the R color channel in the image to be processed The number of pixels in a certain gray scale interval.

The color channel with the largest number of pixels in each gray-scale interval can be determined based on the gray distribution histograms illustrated in FIGS. 3 to 5. For example, in the gray scale interval of 0-8, the color channel with the largest number of pixels is the G channel.

Further, based on the gray distribution histograms shown in FIGS. 3 to 5, the following formulas (6), (7), and (8) can be used to calculate the R channel distribution ratio of each grayscale interval ( _Denoted as R _{P_i} ), G channel distribution ratio (denoted as G _{P_i} ) and B channel distribution ratio (denoted as B _{P_i} ):

In the above formula, i is used to identify the grayscale interval, i is an integer in the range of 1 to 32, for example, R _{P_1} represents the R channel distribution ratio of the first gray-scale interval, R _{P_5} represents the fifth gray The proportion of R channel distribution in the order interval, R _{P_32} represents the proportion of R channel distribution in the 32nd gray order interval.

In the above formula, His _{R_i} represents the number of pixels in the gray-scale interval of the R channel in the i-th gray-scale interval in the image to be processed, and His _{G_i} represents the gray scale in the G-channel in the to-be-processed image. The number of pixels in each gray-scale interval, His _{B_i} represents the number of pixels in the i-th gray-scale interval whose gray level on the B channel in the image to be processed.

By determining the color channel with the largest number of pixels in each grayscale interval, and the calculated ratio of R channel distribution, G channel distribution, and B channel distribution of each grayscale interval, you can get The gray-scale distribution diagram of the pixels in the image to be processed on each color channel shown in FIG. 6. In FIG. 6, the horizontal axis represents the gray scale interval, and the vertical axis represents the distribution ratio of the color channel with the largest number of pixels on the gray scale interval.

By analyzing the grayscale distribution diagram shown in Figure 6, it can be found that the key color channel, for example, the R channel appears on the 6th to 32nd grayscale interval, so that it can be concluded that the pixels in the image to be processed are in the key color The gray scale interval on the channel, R channel, is the 6th to 32nd gray scale interval, which is the gray scale interval of 45-255. In the embodiment of the present disclosure, for the convenience of description, the gray scale interval (such as the gray scale interval 45-255 in FIG. 6) of the key color channel appearing in the gray scale distribution diagram is called the target gray scale interval, and the key color The number of pixels of the channel in the target grayscale interval is greater than the number of pixels of other color channels in the target grayscale interval.

Subsequently, the pixels of the gray level on the R channel in the target gray scale interval of 45-255 can be determined in the image to be processed, and the area composed of these pixels can be determined as the key processing area.

In addition, in the embodiment of the present disclosure, for other regions in the image to be processed except the key processing region, the brightness of any pixel in the other region can be adjusted by using a preset grayscale brightness adjustment curve, for example, As shown in FIG. 7, it is an example of a grayscale brightness adjustment curve.

As shown in FIG. 7, the gray-scale brightness adjustment curve may also include a low-brightness brightness adjustment curve Gray_L, a mid-brightness brightness adjustment curve Gray_M, and a high-brightness brightness adjustment curve Gray_H, based on the above-mentioned components on the key color channel according to the image to be processed The average pixel brightness determines the target brightness adjustment curve. Using the target brightness adjustment curve to adjust the brightness of key processing areas in the image to be processed is similar to the principle. Here, a brightness can be determined based on the gray average pixel brightness of the image to be processed based on FIG. 7 For the adjustment curve, use the determined brightness adjustment curve to adjust the brightness of other areas in the image to be processed except the key processing area, which will not be described in detail in the embodiments of the present disclosure.

It can be seen from the above embodiments that by calculating the gray average pixel brightness of the image to be processed, and the component average pixel brightness of the image to be processed on the R channel, G channel, and B channel; according to the gray average pixel brightness and component average Pixel brightness, determine the key color channel of the image to be processed; determine the target brightness adjustment curve according to the average pixel brightness of the component of the image to be processed on the key color channel; use the target brightness adjustment curve to adjust the brightness of the image to be processed, to achieve the image-based key The color scene enhances the contrast of the image display and enhances the user's viewing experience.

Corresponding to the aforementioned embodiment of the image processing method, the present disclosure also provides an embodiment of the display device.

Embodiments of the display device of the present disclosure may be implemented by software, or by hardware or a combination of hardware and software. Taking software implementation as an example, as a device in a logical sense, it is formed by reading the corresponding computer program instructions in the nonvolatile memory into the memory through the processor of the device where it is located. From a hardware perspective, as shown in FIG. 8, it is a hardware structure diagram of a display device provided by an exemplary embodiment of the present disclosure, except for the processor 801, memory 802, network interface 803, and non-easy In addition to the volatile memory 804 and the internal bus 805, the display device in the embodiment generally may include other hardware according to the actual function of the device, which will not be repeated here.

Please refer to FIG. 9, which is a block diagram of an embodiment of a display device provided by an exemplary embodiment of the present disclosure. As shown in FIG. 9, the device may include: a calculation module 901, a first determination module 902, and a second determination module 903 , And brightness adjustment module 904.

The calculation module 901 is used to calculate the gray average pixel brightness of the image to be processed, and the component average pixel brightness of the image to be processed on the R channel, the G channel, and the B channel respectively;

The first determination module 902 is used to determine the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel, and B channel;

The second determination module 903 is configured to determine a target brightness adjustment curve according to the average pixel brightness of the components of the image to be processed on the key color channel;

The brightness adjustment module 904 is used to adjust the brightness of the image to be processed using the target brightness adjustment curve.

In an embodiment, the first determining module 902 includes (not shown in FIG. 9):

The brightness distribution ratio calculation sub-module is used to calculate the brightness distribution ratio of the image to be processed on the R channel, G channel, and B channel according to the average pixel brightness of the R channel, G channel, and B channel;

The key color channel determination submodule is used to determine the color channels of the R channel, the G channel and the B channel whose brightness distribution ratio is greater than the preset ratio threshold, and the component average pixel brightness is greater than the gray average pixel brightness as the to-be-processed The key color channel of the image.

In an embodiment, the second determination module 903 includes (not shown in FIG. 9):

The interval determination submodule is used to determine the brightness interval to which the average pixel brightness of the component on the key color channel belongs based on the low brightness brightness threshold, the medium brightness brightness threshold and the high brightness brightness threshold corresponding to the key color channel;

The curve determination submodule is used to determine the brightness adjustment curve corresponding to the brightness interval to which the average pixel brightness of the component on the key color channel belongs as the target brightness adjustment curve.

In an embodiment, the first brightness adjustment module 904 includes (not shown in FIG. 9):

The key processing area determination sub-module is used to determine the key processing area in the image to be processed based on the key color channel;

The processing sub-module is used to adjust the brightness of at least one pixel in the key processing area by using the target brightness adjustment curve.

In an embodiment, the critical processing area determination sub-module includes (not shown in FIG. 9):

The statistics submodule is used to separately calculate the grayscale distribution histogram of the image to be processed on the R channel, G channel and B channel. The grayscale distribution histogram is used to represent the grayscale on the color channel in the image to be processed The number of pixels in each gray scale interval;

The color channel determination sub-module is used to determine the color channel with the largest number of pixels on each gray scale interval according to the gray distribution histogram on the R channel, G channel and B channel;

A target interval determination submodule, configured to determine a gray scale interval satisfying the following conditions as the target gray scale interval: the color channel with the largest number of pixels is the key color channel;

The area determination submodule is used to determine, in the image to be processed, an area composed of pixels whose grayscale on the key color channel is in the target grayscale interval as a key processing area.

In an embodiment, the display device further includes (not shown in FIG. 9):

The second brightness adjustment module is used to adjust the brightness of at least one pixel in the area to be processed except the key processing area in the image to be processed using a preset grayscale brightness adjustment curve.

For the implementation process of the functions and functions of each unit in the above display device, please refer to the implementation process of the corresponding steps in the above method for details, which will not be repeated here.

For the device embodiment, since it basically corresponds to the method embodiment, the relevant part can be referred to the description of the method embodiment. The device embodiments described above are only schematics, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located One place, or it can be distributed to multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the objectives of the disclosed solutions. Those of ordinary skill in the art can understand and implement without paying creative labor.

The above are only preferred embodiments of the present disclosure and are not intended to limit the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the present disclosure Within the scope of protection.

Claims

An image processing method, the method includes:

Calculate the grayscale average pixel brightness of the image to be processed, and the component average pixel brightness of the image to be processed on the R channel, the G channel and the B channel respectively;

Determine the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel, and B channel;

Determine the target brightness adjustment curve according to the average pixel brightness of the component of the image to be processed on the key color channel;

Use the target brightness adjustment curve to adjust the brightness of the image to be processed.
The method according to claim 1, said determining the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel and B channel, comprising:

Calculate the proportion of the brightness distribution of the image to be processed on the R channel, G channel, and B channel according to the average pixel brightness of the components on the R channel, G channel, and B channel;

In the R channel, the G channel, and the B channel, the color channel whose brightness distribution ratio is greater than the ratio threshold and the component average pixel brightness is greater than the grayscale average pixel brightness is determined as the key color channel of the image to be processed.
The method according to claim 1, the determining the target brightness adjustment curve according to the component average pixel brightness of the image to be processed on the key color channel comprises:

Determine the brightness interval to which the average pixel brightness of the component on the key color channel belongs based on the low brightness brightness threshold, the medium brightness brightness threshold and the high brightness brightness threshold corresponding to the key color channel;

The brightness adjustment curve corresponding to the brightness interval to which the component average pixel brightness on the key color channel belongs is determined as the target brightness adjustment curve.
The method according to claim 1, the performing brightness adjustment on the image to be processed using the target brightness adjustment curve includes:

Determine a key processing area in the image to be processed based on the key color channel;

Use the target brightness adjustment curve to adjust the brightness of at least one pixel in the critical processing area.
The method according to claim 4, the determining the key processing area in the image to be processed based on the key color channel comprises:

Count the grayscale distribution histograms of the image to be processed on the R channel, G channel, and B channel respectively. The grayscale distribution histogram is used to indicate that the grayscale on the color channel is in each gray in the image to be processed. The number of pixels in the order interval;

Determine the color channel with the largest number of pixels on each gray-scale interval according to the gray distribution histogram on the R channel, G channel and B channel;

The gray scale interval satisfying the following conditions is determined as the target gray scale interval: the color channel with the largest number of pixels is the key color channel;

In the image to be processed, an area composed of pixels on the key color channel whose gray level is within the target gray scale interval is determined as a key processing area.
A display device, including: a processor, a memory and a display;

The memory is connected to the processor and configured to store computer instructions;

The processor, connected to the memory and the display, is configured to execute the computer instructions to cause the display device to:

Calculate the grayscale average pixel brightness of the image to be processed, and the component average pixel brightness of the image to be processed on the R channel, the G channel and the B channel respectively;

Determine the key color channel of the image to be processed according to the gray average pixel brightness and the component average pixel brightness on the R channel, G channel, and B channel;

Determine the target brightness adjustment curve according to the average pixel brightness of the component of the image to be processed on the key color channel;

Use the target brightness adjustment curve to adjust the brightness of the image to be processed.
The display device of claim 6, the processor is further configured to execute the computer instructions to cause the display device to:

Calculate the proportion of the brightness distribution of the image to be processed on the R channel, G channel and B channel according to the average pixel brightness of the components on the R channel, G channel and B channel;

In the R channel, the G channel, and the B channel, the color channel whose brightness distribution ratio is greater than the ratio threshold and the component average pixel brightness is greater than the grayscale average pixel brightness is determined as the key color channel of the image to be processed.
The display device of claim 6, the processor is further configured to execute the computer instructions to cause the display device to:

Determine the brightness interval to which the average pixel brightness of the component on the key color channel belongs based on the low brightness brightness threshold, the medium brightness brightness threshold and the high brightness brightness threshold corresponding to the key color channel;

The brightness adjustment curve corresponding to the brightness interval to which the component average pixel brightness on the key color channel belongs is determined as the target brightness adjustment curve.
The display device of claim 6, the processor is further configured to execute the computer instructions to cause the display device to:

Determine a key processing area in the image to be processed based on the key color channel;

Use the target brightness adjustment curve to adjust the brightness of at least one pixel in the critical processing area.
The display device of claim 9, the processor is further configured to execute the computer instructions to cause the display device to:

Count the grayscale distribution histograms of the to-be-processed image on the R channel, G channel, and B channel respectively. The grayscale distribution histogram is used to indicate that the grayscale on the color channel is in each gray in the to-be-processed image. The number of pixels in the order interval;

Determine the color channel with the largest number of pixels on each gray scale interval according to the gray distribution histogram on the R channel, G channel and B channel;

The gray scale interval satisfying the following conditions is determined as the target gray scale interval: the color channel with the largest number of pixels is the key color channel;

In the image to be processed, an area composed of pixels on the key color channel whose gray level is within the target gray scale interval is determined as a key processing area.
A computer-readable non-volatile storage medium having computer instructions stored thereon, which when executed by a processor implements the method of any one of claims 1 to 5.