WO2023124722A1 - Image processing method and apparatus, electronic device, and computer-readable storage medium - Google Patents

Abstract

An image processing method, comprising: obtaining enhancement preference information of a user (102); obtaining an image to be processed, and dividing, according to the hue distribution of said image, said image into a plurality of areas to be enhanced (104); and performing corresponding color enhancement processing on each of said areas according to the enhancement preference information to adjust the color attribute of said image (106).

Description

Image processing method, device, electronic device, and computer-readable storage medium

Cross References to Related Applications

This application claims the priority of the Chinese patent application with the application number 2021116768158 and the title of the invention "image processing method, device, electronic device and computer-readable storage medium" submitted to the China Patent Office on December 31, 2021, the entire content of which Incorporated in this application by reference.

technical field

The present application relates to the field of display technology, in particular to an image processing method, device, electronic equipment and computer-readable storage medium.

Background technique

With the development of display technology, display devices can present more and more rich colors. Users have different preferences for colors, for example, some people prefer bright colors, while others prefer more natural colors. However, the image processing method in the current display device is single, and cannot be flexibly adapted to users with different preferences, resulting in poor viewing experience for users.

The statements herein merely provide background information related to the present application and do not necessarily constitute exemplary techniques.

Contents of the invention

According to various embodiments of the present application, an image processing method, device, electronic equipment, computer-readable storage medium, and computer program product are provided.

An image processing method, the method comprising:

Obtain the user's enhanced preference information;

Acquiring an image to be processed, dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed;

Perform corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

An image processing device, the device comprising:

A preference acquisition module, configured to acquire enhanced preference information of the user;

An area division module, configured to acquire an image to be processed, and divide the image to be processed into a plurality of areas to be enhanced according to the tone distribution of the image to be processed;

An enhancement processing module, configured to perform corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

A display device comprising:

display screen;

A processor, connected to the display screen, configured to acquire user enhancement preference information; acquire an image to be processed, and divide the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed; The enhancement preference information performs corresponding color enhancement processing on each of the regions to be enhanced, so as to adjust the color attribute of the image to be processed; and sends the image with the adjusted color attribute to the display screen for display.

An electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method are realized.

The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below. Other features, objects and advantages of the present application will be apparent from the description, drawings and claims.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments or exemplary technologies of the present application, the following will briefly introduce the accompanying drawings that need to be used in the descriptions of the embodiments or exemplary technologies. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present application. Those skilled in the art can also obtain the drawings of other embodiments according to these drawings without creative work.

Fig. 1 is one of flow charts of the image processing method of an embodiment;

Fig. 2 is a subflow chart of step 102 of an embodiment;

Fig. 3 is the second flowchart of the image processing method of an embodiment;

Fig. 4 is the third flowchart of the image processing method of an embodiment;

FIG. 5 is a fourth flowchart of an image processing method of an embodiment;

Fig. 6 is a frame diagram of the internal structure of a display device according to an embodiment;

FIG. 7 is an internal structural diagram of an electronic device according to an embodiment.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application 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 application, and are not intended to limit the present application.

The image processing method provided in the embodiment of the present application may be applied to a display device. Among them, the display device can be but not limited to various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, etc. . Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, and the like. The display device includes at least a display screen for displaying images and a processor for processing image data. Specifically, the processor may include a GPU (Graphics Processing Unit, graphics processing unit), and the GPU is used to perform mathematical and geometric calculations and graphics rendering, so as to realize required image processing functions.

FIG. 1 is one of the flowcharts of an image processing method in an embodiment. Referring to FIG. 1 , in this embodiment, the image processing method includes steps 102 to 106 .

Step 102, acquiring enhanced preference information of the user.

The user's enhancement preference information refers to the user's preference information for color enhancement. Specifically, the user's physiological phenomena and/or psychological feelings may lead to different preferences for different color enhancement methods. Physiological phenomenon refers to the phenomenon that the color observed by human eyes is not exactly the same for the same objective color under the same observation environment. Exemplarily, physiological phenomena that can cause differences in observed colors include, for example, race, age, color vision impairment, and the like. Psychological feeling refers to the user's subjective feeling of different colors. For example, some people like bright colors and some people like natural colors. Moreover, people who like bright colors may not like bright colors for all colors, but prefer natural skin tones and bright blue sky and trees.

Exemplarily, the user's enhanced preference information can be obtained according to historical data. For example, the user's historical image editing operations in the system image processing software or third-party image processing software can be obtained, and the user's enhancement preference information can be obtained according to the user's color adjustment during the editing operation. The user's adjustment of the color may specifically be the adjustment of each color attribute. If the user frequently chooses to increase the brightness of the red channel when making adjustments, it means that the user prefers brighter colors for the red channel. In another example, some questions or pictures related to color enhancement preference may also be provided to the user, and enhancement preference information may be obtained according to the selection result provided by the user. It can be understood that the above method of obtaining enhanced preference information of users is only for illustrative purposes, and is not intended to limit the scope of protection of this embodiment, and other methods capable of obtaining enhanced preference information of users can also be applied to this embodiment middle. Therefore, by determining the enhancement preference information of the user in a certain way, a personalized and accurate color enhancement effect can be provided according to the preference of the user.

Step 104, acquire the image to be processed, and divide the image to be processed into multiple regions to be enhanced according to the tone distribution of the image to be processed.

Specifically, as described above, the same user has different perceptions of the brightness of different colors. Therefore, if color enhancement processing is performed on different colors in the same manner, a better color enhancement effect cannot be presented. For example, take the case that users prefer natural skin tones and vivid landscapes. If the color enhancement processing parameters for the skin color are used to perform the same color enhancement processing on the entire image, the color brightness of the landscape area will be insufficient, that is, the color of the landscape area will not be bright enough. If the color enhancement processing parameters for the landscape are used to perform the same color enhancement processing on the entire image, the color brightness of the skin color area will be too high, that is, the color of the skin color area will be distorted. Among them, hue (Hue) refers to the attribute of the color, which describes the pure color appearance, or can be understood as the position of the spectral color. Therefore, different colors can be understood as colors with different hues. By dividing the image to be processed into multiple areas to be enhanced based on the hue, it is possible to effectively avoid that the same processing parameters are used to process colors with different hues. Enhance the effect of a single problem, so as to further improve the effect of color enhancement.

Step 106: Perform corresponding color enhancement processing on each region to be enhanced according to the enhancement preference information, so as to adjust the color attribute of the image to be processed.

Specifically, the processor may be pre-configured with a mapping relationship between different hues and color enhancement processing parameters, so as to perform corresponding color enhancement processing for different areas to be enhanced during the image processing process. That is, for the region to be enhanced with the first hue, the corresponding first parameter is selected for color enhancement processing; for the region to be enhanced with the second hue, the corresponding second parameter is selected for color enhancement processing, and so on. Also, by combining enhancement preference information, more accurate color enhancement processing can be achieved. Exemplarily, the first hue may be configured with multiple different color enhancement processing parameters, and different parameters correspond to different enhancement preference information respectively.

In this embodiment, by dividing the image to be processed into multiple areas to be enhanced based on the tone distribution of the image to be processed, corresponding color enhancement processing can be performed for different tones, thereby effectively avoiding the Problems with color distortion. Moreover, in combination with the obtained enhancement preference information of the user, a personalized and accurate color enhancement effect can be provided according to the preference of the user. Therefore, in the embodiment of the present application, accurate color enhancement processing can be performed according to the tone distribution in the image to be processed and the user's enhancement preference information, thereby realizing an image processing method with a high degree of personalization and high color reproduction.

FIG. 2 is a subflow chart of step 102 in one embodiment. Referring to FIG. 2 , in one embodiment, the step of acquiring user's enhanced preference information includes step to step.

Step 202, generating a candidate image set.

Wherein, the candidate image set includes multiple images generated by using multiple different color enhancement processes on the same image. The candidate image set is used for displaying on a user interface (User Interface, UI), and the user can realize interaction by clicking a trigger area on the interface. Optionally, the candidate image set may be generated in response to a preset operation acting on the user interface. The preset operation may be, for example, the user clicking a color personalization button, or the user performing a gesture corresponding to the color personalization. Examples are not limited.

Each candidate image set may include two, three, or four images, and specifically, an appropriate number of images may be selected according to the analysis accuracy and speed requirements of the enhanced preference information. Among them, multiple images in the same candidate image set can be used to test the user's specific preference for some color attributes. Exemplarily, the saturation of the blue channel of the same image can be adjusted to generate three images in the same candidate image set, for example, the saturation of the blue channel can be set to 100%, 95% and 90% respectively , and keep the parameters of other color channels unchanged. Wherein, the initial image used to generate the candidate image set may be a color patch image, that is, the initial image includes color patches of colors related to the color attribute to be tested. The initial image can also be a photo that satisfies preset conditions. For example, if you need to test the color attributes related to the blue tone, you can use an image related to the sky or the ocean as the initial image; if you need to test the color attributes related to the green tone, you can use plants The relevant image is used as the initial image. Optionally, multiple images in the same candidate image set may be displayed on the user interface at the same time, or may be displayed sequentially on the user interface, which is not limited in this embodiment.

Moreover, when the candidate image set is displayed, the user may be prompted to make a selection according to personal preference, so as to obtain the user's preference selection result in a timely manner. For example, when displaying multiple photos in the candidate image set, the user may be notified of the image selection rules and prompted to make a selection through text prompts. The text prompts may be, for example, "Please select your favorite image", "Please Select the image you don't like the most" and "Please sort the images according to your preference", etc., to realize a user-friendly interface.

Optionally, when multiple candidate image sets need to be generated, the multiple candidate image sets can be generated simultaneously to simplify the generation rules of the candidate image sets; multiple candidate image sets can also be generated sequentially. Among them, if multiple candidate image sets are sequentially generated, multiple images in the subsequent candidate image set can be adaptively generated according to the preference selection results of the previous candidate image sets, so as to improve the analysis of enhanced preference information accuracy.

Step 204, obtain the user's preference selection results for multiple images in each candidate image set, and obtain enhanced preference information according to the preference selection results.

Specifically, when the enhanced preference information is acquired based on the user's preference selection result of the candidate image set, it may correspond to the image selection rule previously notified to the user. For example, if the selection rule is to select a favorite image, the color attribute corresponding to the selected image can be enhanced; if the selection rule is to select an unfavorable image, the color attribute corresponding to the selected image can be weakened.

It is understandable that ordinary users have no specific research on color attributes. If the concrete presentation method of this embodiment is not adopted, but only controls such as sliders for adjusting attribute parameters are provided, users cannot understand what will happen after these adjustments. What kind of effect will be produced, and whether there will be side effects is unknown, so that the user cannot realize accurate adjustment of the color enhancement effect. Therefore, in this embodiment, by providing alternative image sets, the user can have a more intuitive feeling for different color enhancement processes, so that the user can achieve a more accurate choice, and then can obtain more accurate enhancement preference information, and It can effectively improve the user's convenience of use.

In one embodiment, there are multiple candidate image sets, wherein the color enhancement processing parameters corresponding to multiple images in the n+1th candidate image set are determined by the preference selection result of the nth candidate image set. Specifically, this embodiment may include the following steps when generating the candidate image set. First, the first candidate image set is generated, and then according to the user's preference selection results for multiple images in the nth candidate image set, various color enhancement processing parameters of the n+1th candidate image set are determined and corresponding multiple color enhancement processing parameters are generated. images, n is a positive integer. Wherein, multiple candidate image sets are used to be displayed on the user interface sequentially, that is, the nth candidate image set is displayed on the user interface first, and the user provides preference selection for multiple images in the nth candidate image set After the results are obtained, multiple graphics in the n+1th candidate image set are determined, and the n+1th candidate image set is displayed on the user interface until all the candidate image sets are displayed. For example, if the user's preference selection result for multiple images in the first candidate image set is that he prefers images with higher blue saturation, then when generating the second candidate image set, the blue color of each image may be The saturation of the color channels is adjusted to the user's preference, and the red channel of each image is further adjusted to have different saturations, so as to obtain the user's enhancement preference information more quickly and accurately. It can be understood that, in some embodiments, the multiple candidate image sets may only be displayed sequentially, and the multiple candidate image sets are not related to each other when they are generated.

In one embodiment, the number of candidate image sets is two. Specifically, FIG. 3 is a second flowchart of an image processing method in an embodiment. Referring to FIG. 3 , in this embodiment, the image processing method includes step 302 to step 310 . Wherein, the specific implementation manners of step 306 to step 310 can refer to the above-mentioned embodiment, which will not be repeated here. Step 202 in the above-mentioned embodiment can include step 302 to step 304 of this embodiment.

Step 302, generating a first candidate image set according to the first initial image with a blue-green tone.

Wherein, the appropriate first initial image may be determined according to the ratio of the number of pixels displayed in the blue and green hue range to the total number of pixels in the display screen. Specifically, the above ratio may be 90%, that is, 90% of the pixels in the display screen are used to display blue-green hues. Exemplarily, the first initial image may be, for example, an image of blue sky and trees, and by performing a variety of different color enhancement processes on the image of blue sky and trees, the required first candidate image set can be generated, thereby obtaining the user's preference for blue-green tones. preference.

Step 304, generating a second set of candidate images according to the second initial image of the red, green and blue tone and the second parameters.

Wherein, the appropriate second initial image can be determined according to the ratio of the number of pixels displayed in the red, green, and blue tonal range to the total number of pixels in the display screen. Specifically, if the number of pixels displayed as a red tone in the image accounts for 25% to 35% of the total number of pixels on the display screen, the number of pixels displayed as a green tone also accounts for 25% to 35% of the total number of pixels on the display screen, and If the number of pixels displayed as blue tone accounts for 25% to 35% of the total number of pixels in the display screen, it can be considered that the image can be used as the second initial image. Exemplarily, the second initial image may be, for example, an image containing red, green, blue and other colored fruits, and by performing a variety of different color enhancement processes on images containing red, green, blue and other colored fruits, the first initial image may be generated. Two candidate image sets, the second candidate image set is used to obtain the user's preference for red, green and blue tones.

Step 306, obtaining the user's preference selection results for multiple images in each candidate image set, and obtaining enhanced preference information according to the preference selection results.

Step 308, acquire the image to be processed, and divide the image to be processed into multiple regions to be enhanced according to the tone distribution of the image to be processed.

Step 310: Perform corresponding color enhancement processing on each region to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

Further, in one of the embodiments, the second parameter of the color enhancement process may be determined according to the user's preference selection result of multiple images in the first candidate image set, and the second parameter of the color enhancement process may be determined according to the determined second parameter and the first red, green and blue tone. The second candidate image set is generated from the two initial images, thereby improving the pertinence of the second candidate image set and the accuracy of the selection result.

In one of the embodiments, multiple images in the candidate image set are respectively configured with corresponding multiple image enhancement coefficients in one-to-one correspondence. Wherein, the image enhancement coefficient corresponds to the color enhancement processing parameter one by one. That is, if the user selects an image generated based on a certain color enhancement processing parameter, it can be understood that the user selects the image enhancement coefficient corresponding to the parameter as the preference selection result. Correspondingly, if a certain target enhancement coefficient ratio is determined based on the user's preference selection result, then a color enhancement processing parameter corresponding to the target enhancement coefficient ratio may also be determined, and the image to be processed is processed. FIG. 4 is a third flowchart of an image processing method in an embodiment. Referring to FIG. 4 , in one embodiment, the image processing method includes steps 402 to 412 . Wherein, the specific implementation manners of steps 402 to 404, and steps 410 to 412 can refer to the foregoing embodiments, which will not be repeated here, that is, the steps in the foregoing embodiments to obtain enhanced preference information according to the preference selection results specifically include this embodiment Step 406 to step 408 of the example.

Step 402, generating a candidate image set.

Step 404, obtaining the user's preference selection results for multiple images in each candidate image set.

Step 406, acquiring candidate enhancement coefficients corresponding to each candidate image set respectively.

Wherein, the candidate enhancement coefficient is an image enhancement coefficient corresponding to an image selected by the user from the candidate image set. Exemplarily, it is assumed that the number of candidate image sets is two, and each candidate image set includes three images as an example. Wherein, the image enhancement coefficients of the three images in the first candidate image set are 0.2, 0.5 and 0.8 respectively, and the image enhancement coefficients of the three images in the second candidate image set are 0.2, 0.7 and 0.9 respectively. If the user selects an image with an image enhancement factor of 0.5 in the first candidate image set, the first candidate enhancement factor is 0.5; if the user selects an image with an image enhancement factor of 0.7 in the second candidate image set, then the second candidate image set The selected enhancement factor is 0.7.

In step 408, a target enhancement coefficient ratio is obtained as enhancement preference information according to multiple candidate enhancement coefficients. Exemplarily, based on the two candidate enhancement coefficients obtained in the previous step, an average value of the two enhancement coefficients of 0.6 may be used as the target enhancement coefficient ratio for subsequent color enhancement processing. It can be understood that, the average manner of obtaining the target enhancement coefficient ratio may be, but not limited to, an arithmetic average, a weighted average, and the like. Among them, by avoiding the value of the image enhancement coefficient, the situation of obtaining the same target enhancement coefficient ratio after selecting different images can be avoided, so as to improve the reliability of the acquired target enhancement coefficient ratio, thereby improving the reliability of the image processing method sex.

Step 410, acquire the image to be processed, and divide the image to be processed into multiple regions to be enhanced according to the tone distribution of the image to be processed.

Step 412: Perform corresponding color enhancement processing on each region to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

In this embodiment, by setting the enhancement coefficient, the connection between the user's personalized selection and the color enhancement processing parameters can be established. Therefore, by relatively simple calculation of the preference selection results of multiple candidate image sets, the required target enhancement coefficient can be obtained, and accurate color enhancement processing can be realized through the obtained target enhancement coefficient.

In one of the embodiments, the step of obtaining the enhanced preference information of the user may further include the following steps. If a coefficient adjustment signal acting on a designated trigger area of the interface is received, the target enhancement coefficient ratio is updated according to the coefficient adjustment signal. Exemplarily, the designated trigger area may be, for example, a slider area on the user interface. There are multiple scales in the slider area, and the user can select any scale on the slider by dragging. Wherein, each scale on the slider corresponds to each target enhancement coefficient ratio. For example, the slider may be provided with 256 scales, and the 256 scales correspond to 256 target enhancement coefficient ratios one-to-one, and the 256 target enhancement coefficient ratios correspond to 256 color enhancement processing parameters respectively. Therefore, by selecting a scale, a corresponding color enhancement processing parameter can be selected, thereby realizing the selection of the color enhancement effect.

Further, a preliminary target enhancement coefficient ratio may be firstly determined based on the candidate image set. For example, if the number of candidate image sets is two, and each candidate image set includes 3 images, it may be determined that the preliminary target enhancement coefficient ratio is one of 9 values. Moreover, the target enhancement coefficient ratio preliminarily determined through the above steps is 9 out of the 256 target enhancement coefficient ratios corresponding to the 256 scales, thereby preliminarily determining the value range of the target enhancement coefficient ratio. Based on the preliminarily determined value range, the user can further fine-tune the adjustment through the slider, thus realizing the fine-tuning of the color enhancement effect. In this embodiment, through the combination of the above two methods for determining the target enhancement coefficient ratio, the required color enhancement processing parameters can be determined quickly and accurately.

In one embodiment, the step of performing corresponding color enhancement processing on each area to be enhanced according to the enhancement preference information may include the following steps. A color correction matrix corresponding to the target enhancement coefficient ratio is acquired, and color enhancement processing is performed according to the color correction matrix corresponding to each area to be enhanced.

That is, in this embodiment, the color enhancement processing parameter is a color correction matrix. Wherein, each color correction matrix corresponds to at least one region to be enhanced. The color correction matrix (ColorCorrection Matrix, CCM) can correct the image with lower saturation to the image with higher saturation. That is, the above correction can be understood as a process of mapping an image with lower saturation to an image with higher saturation through a preset mapping relationship. Also, the same color can be adjusted to different degrees based on different color correction matrices. The color correction matrix can be generated by means of, for example, a three-dimensional look-up table (3D Look UpTable, 3D-Lut). Specifically, the source color space with low saturation can be divided into multiple grids, and the target color space with high saturation can also be divided into multiple grids, and a one-to-one mapping relationship between the grids can be established. That is, a certain grid in the source color space corresponds to a certain grid in the target color space. In this embodiment, the image to be processed can be understood as an image with low saturation. Therefore, the corresponding target enhancement coefficient ratio can be obtained through the user's enhancement preference information, and one or more corresponding color correction matrices can be determined according to the preset rules and the target enhancement coefficient ratio, so that personalization can be performed through an appropriate color correction matrix color enhancement processing.

Specifically, as mentioned in the foregoing description, the same person may have different requirements for different hues. Therefore, under some target enhancement coefficient ratios, different color correction matrices may be used for different regions to be enhanced; and under other target enhancement coefficient ratios, the same color correction matrix may be used for all regions to be enhanced. Therefore, in this embodiment, based on the above manner of selecting the color correction matrix, different color enhancement processes can be performed on different regions, thereby improving the overall effect of the color enhancement process.

In one embodiment, the perception of the three primary colors by human eyes can be integrated into the color calibration matrix to achieve more accurate color calibration. Among them, the 24-color standard color card can be photographed at a certain color temperature to obtain the 24-color RGB information of the camera, and then the colorimeter is used to measure and obtain 24 groups of CIE1931XYZ tristimulus values of the 24-color standard color card. Wherein, the XYZ tristimulus value can be understood as being obtained jointly according to the RGB information and the human eye matching function. Therefore, based on the above data, a mapping relationship between RGB information and XYZ tristimulus values that can reflect human perception can be established, and this mapping relationship can be used as one of the factors for establishing a color calibration matrix, so as to achieve a more accurate color enhancement effect.

In one of the embodiments, before dividing the image to be processed into a plurality of areas to be enhanced according to the tone distribution of the image to be processed, it also includes obtaining the skin color area in the image to be processed, and adjusting the color attributes of the skin color area to enhance the color of the skin color area. Apply color protection. Wherein, the skin color area refers to the area where human body skin color exists in the image. It is understandable that during the process of color enhancement processing, the color attributes of each region will be adjusted, but excessive color enhancement may lead to distortion of skin color and affect the user's viewing experience. Therefore, in this embodiment, by screening and protecting the skin color area, the problem of skin color distortion can be effectively avoided, thereby improving the display quality.

Optionally, the skin color region may be determined according to the current color space and the corresponding threshold condition in the space. For example, if the current color space is the RGB color space, the skin color area can be determined by the following threshold conditions R>95, G>40, B>20, where R>G, R>B, Max(R,G,B )-Min(R,G,B)>15 and Abs(R-G)>15. If the current color space is the HSV color space, the skin color area 7<H<20, 28<S<256 and 50<V<256 can be determined by the following threshold conditions. It can be understood that the above example is only used for illustration and not for limiting the scope of protection of this embodiment. In other embodiments, the color space may also be a color space such as YCrCb and a corresponding threshold condition is set.

FIG. 5 is a fourth flowchart of an image processing method in an embodiment. Referring to FIG. 5 , in one embodiment, in one embodiment, the image processing method includes steps 502 to 520 . Wherein, for the specific implementation manners of steps 502 to 508, and steps 518 to 520, reference may be made to the above-mentioned embodiments, and details are not repeated here, that is, before the steps in the above-mentioned embodiments divide the image to be processed into a plurality of regions to be enhanced, , further including steps 510 to 516 of this embodiment.

Step 502, generating a candidate image set.

Step 504, obtaining the user's preference selection results for multiple images in each candidate image set.

Step 506, acquiring candidate enhancement coefficients corresponding to each candidate image set respectively.

In step 508, a target enhancement coefficient ratio is obtained as enhancement preference information according to multiple candidate enhancement coefficients.

Step 510, acquire the image to be processed, and convert the image to be processed from the RGB color space to the target color space.

Wherein, the target color space is an HSI color space or an HSV color space. Taking the HSV color space as an example, H (Hue) is the hue value, which refers to the attribute of the full color of the color. Each color corresponds to a different hue value, and the value ranges from 0° to 359°. S (Saturation) is the saturation value, which refers to the degree of dilution by white. The greater the dilution, the less the saturation, and it will be closer to the center point. The value ranges from 0 to 1. V (Value) is the brightness of the color, the brighter the color, the higher the brightness, and vice versa, the value ranges from 0 to 1. Among them, the conversion relationship formula between RGB color space and HSV color space is as follows, where max is the maximum value among R, G, and B, and min is the minimum value among R, G, and B.

v=max

Step 512, acquiring the skin color area in the image to be processed.

It can be understood that the image to be processed is currently in the HSV color space, that is, the skin color region is determined based on the aforementioned threshold condition in the HSV color space. Moreover, based on the definitions of the aforementioned three components of H, S, and V, it can be seen that each component in the HSV color space is not related to each other. Therefore, compared with the RGB color space, the HSV color space is less susceptible to the influence of light. By converting the RGB color gamut to the HSV color gamut, the influence of light on the image can be effectively reduced, and the misjudgment of the skin color area can be avoided. .

Step 514, adjusting the saturation and/or lightness of the skin color area.

Step 516, converting the image after adjusting the color attributes of the skin color area from the target color space to the RGB color space.

Step 518: Divide the image converted back into the RGB color space into multiple regions to be enhanced according to the hue.

Step 520: Perform corresponding color enhancement processing on each region to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

In this embodiment, the skin color area is defined in the HSV color space, and the skin color area is protected, which can enhance the color saturation while preventing the skin color area from being over-emphasized, thereby maintaining the naturalness of the skin color.

In one of the embodiments, the above-mentioned color space conversion operation can be realized through an analog circuit, that is, a corresponding analog circuit is constructed based on the conversion logic of the color space, so that the conversion of the color space is realized through the analog circuit. It can be understood that the processor only supports operations on digital signals. Therefore, if a processor is used to realize the conversion operation of the above color space, it is necessary to convert the analog signal into a digital signal for operation. However, taking 256 gray levels as an example, two analog signals that are similar but actually different may be converted into digital signals at the same gray level after digital-to-analog conversion, resulting in partial data loss. Moreover, when performing color space conversion, two different colors in the original color space may be mapped to two very similar colors in the new color space, resulting in the loss of some colors. Therefore, through the above-mentioned multiple conversion operations, the digital signal will have relatively large data loss. In this embodiment, the conversion operation of the color space is realized by the analog circuit, which can effectively avoid the loss of some data, thereby improving the accuracy of the data processing process. Moreover, the operation process of the analog circuit does not require clock control, so the calculation speed is relatively fast.

In one embodiment, the step of dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed includes: dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed and at least one transition zone. Correspondingly, the image processing method further includes: smoothing the color attributes of the transition regions according to the color attributes of the plurality of regions to be enhanced after the color enhancement processing.

It is understandable that if the color correction matrix covers too many tonal areas, it may cause the color correction matrix to be too large, and the amount of calculation will increase greatly, which will affect the speed of color enhancement. However, if the color correction matrix is reduced, some colors will The enhancement effect is not good. Therefore, the color correction matrix can usually only cover part of the key tonal regions (ie, regions to be enhanced). In order to balance the relationship between operation speed and accuracy, usually the color correction matrix only covers 24 tonal regions. Therefore, there are usually some areas in the image to be processed that do not have corresponding color correction matrices. In this embodiment, for the above-mentioned transition area, based on the color enhancement result of the area to be enhanced, the enhancement may be performed by means of smoothing, so as to realize the color enhancement of the entire image to be processed. Wherein, the manner of the smoothing processing may adopt any manner with a smoothing effect such as interpolation, which is not limited in this embodiment.

Further, when using the HSV color space for skin color protection, in the HSV color space, only the S component and V component of the skin color area can be adjusted, and the H component of the skin color area can be kept unchanged to ensure the accuracy of the skin tone . After the skin color protection is completed and converted back to the RGB color space, the smoothing of the skin color area and the smoothing of the transition area are realized by one smoothing process to reduce the number of times of smoothing, thereby improving the speed of the image processing method.

In one of the embodiments, the image processing method further includes a step of platform verification. Specifically, when the platform adjusts the parameters of the color calibration matrix, the color information of the processed image can be detected by a color analyzer to determine whether the image generated by the color enhancement process meets the requirements. For example, it can be detected whether the boundary between the transition area and the area to be enhanced is sufficiently smoothed. Optionally, the step of platform verification can be set before skin color protection, or can be executed synchronously with skin color protection. In this embodiment, by setting the platform verification step, the reliability and accuracy of the image processing algorithm can be verified before the display device leaves the factory, thereby improving user experience.

In one of the embodiments, the image processing method further includes the following steps. Perform color enhancement processing on the image to be processed according to the current preset color effect of the display screen to generate a first enhanced image, and fuse the first enhanced image and the second enhanced image according to the target enhancement coefficient ratio to generate a third enhanced image.

Wherein, the preset color effect refers to a basic color effect set by default when the display device leaves the factory. That is, the preset color effect can be understood as a color effect that has nothing to do with the user's enhanced preference information, for example, it can include a night effect, a dusk effect, and the like. The second enhanced image is an image generated by performing corresponding color enhancement processing on each area to be enhanced according to the enhancement preference information. Specifically, the basic effect can be called 3DLut_CC, and the color enhancement effect based on the enhancement preference information can be called 3DLut_ENIR, and the two are combined to obtain the total enhancement effect 3DLut_OUT=3DLut_CC+Delta0+Ratio*Delta1 through the steps of this embodiment. Among them, Delta0=3DLutENIR0-3DlutCC, Delta1=3DLutENIR1-3DLutENIR0, 3DLutENIR0 refers to the final effect of the weakest color enhancement, and 3DLutENIR1 refers to the final effect of the strongest color enhancement. Therefore, the fusion of different enhancement effects can be realized based on the above formula, that is, the fusion of the first enhanced image and the second enhanced image based on the target enhancement coefficient ratio is realized.

In one of the embodiments, the image processing method further includes the following steps. When the target enhancement coefficient ratio is equal to the coefficient threshold, the target color gamut supported by the display screen is obtained, and if the target color gamut is larger than the color gamut of the image after color enhancement processing, the color gamut of the image after color enhancement processing is extended. For example, if the target color gamut natively supported by the display is 110% NTSC, and the color gamut range of 3DLut_CC is 90% NTSC, then the color gamut can be extended to 100% NTSC when the color enhancement effect is the strongest , to adjust in conjunction with the hardware of the display to achieve better color rendering.

In one of the embodiments, the display screen can also have an IR-drop adjustment function. Specifically, in a display screen with an active matrix organic light emitting diode (Active Matrix Organic Light Emitting Diode, AMOLED) structure, when the current is transmitted along the circuit trace, the impedance of the circuit trace will cause a voltage drop, which A voltage drop phenomenon can be called IR-drop (voltage drop). Therefore, the display driver chip can be used to control the IR-drop of the display screen to be turned on or off, so as to control the display effect. Specifically, when the IR-drop compensation function of the display screen is turned off, that is, when there is an IR-drop on the display screen, the pixel brightness of the three colors R, G, and B satisfies the following relationship: R+G+B=xW. Wherein, x is a fixed value approximately equal to 1.4, and the specific value of the fixed value is determined by the circuit design of the display screen. Therefore, based on the above relational formula, it can be seen that when the IR-drop compensation function of the display screen is turned off, the contrast ratio of the display screen is the highest. When the IR-drop compensation function of the display is turned on, that is, when there is no IR-drop on the display, the contrast of the display is the lowest, and the image after color enhancement processing lacks a sense of hierarchy. Based on the above, it can be found that if only two states of the IR-drop compensation function are enabled and disabled, the display effect will be extreme and the display flexibility will be insufficient.

Therefore, in this embodiment, the stepless adjustment function of the IR-drop can be used to realize the flexible adjustment of the contrast to improve the display quality. Optionally, before skin color protection, an instruction can be issued to enable the stepless adjustment function of IR-drop. Among them, when the adjustment function is just turned on, the initialization state is that the IR-drop compensation function is off, that is, the contrast of the display screen is the largest, and after completing the steps of performing corresponding color enhancement processing on each area to be enhanced according to the enhancement preference information , adjust the degree of IR-drop according to the enhanced image, thereby changing the contrast of the display screen. Specifically, the IR-drop adjustment in the image processing method may include the following steps. The average image level of the image after the color enhancement processing is obtained, and the brightness of each color channel is adjusted respectively according to the average image level, so as to adjust the contrast of the image after the color enhancement processing.

Among them, the average picture level (Average Picture Level, APL) refers to the average value of the gray scale of all pixels in the image after the current color enhancement process. When obtaining the average image level, you can first obtain the gray scale and total number of pixels of each pixel in the image after the current color enhancement process, and calculate the current color enhancement process based on the gray scale and total number of pixels of each pixel. The average grayscale of the resulting image. For example, the gray levels of all pixels in the image can be accumulated, and the accumulated value can be divided by the total number of pixels in the image to obtain the average gray level of the image.

Wherein, the brightness of each color channel can be adjusted by adjusting the gamma value. Specifically, in a low-brightness environment, the human eye is sensitive to brightness changes and can perceive small brightness differences, but in a high-brightness environment, it is not sensitive to brightness changes, and the human eye can only distinguish when the brightness value changes greatly. The above characteristics can be referred to as gamma (Gamma) characteristics. Therefore, if it is necessary to obtain a uniformly changing brightness experience, then the brightness displayed by the display needs to change non-uniformly to adapt to the Gamma characteristics of the human eye, and the nonlinear relationship parameter between brightness and gray scale is the gamma value. Therefore, after obtaining the gamma correction value of the image after the current color enhancement processing, the gamma correction curve corresponding to the gamma correction value can be drawn according to the gamma correction value, and the gamma correction curve is the gamma of the image Correction curve, according to the gamma correction curve, the target brightness corresponding to the pixels of different gray scales in the image can be obtained, and the current brightness of the pixels of different gray scales in the image can be adjusted to the target brightness, so as to realize the adjustment of the brightness of the image. The adjustment can accurately display the brightness of pixels of different gray scales in the current color-enhanced image, so that the change of brightness conforms to human perception, and the color transparency and light-shadow relationship of the image are improved, making the contrast of the image more perfect. Intense and vivid, optimize the display effect of the monitor.

In this embodiment, by obtaining the average gray scale of the display image, the gamma correction value of the image can be obtained according to the average gray scale of the image, and the brightness of the current color-enhanced image can be adjusted according to the gamma correction value of the image. Adjustment, so as to optimize the display effect of the display on the basis of retaining the IR-drop characteristics of the display, so that the contrast of the image after the color enhancement processing is more vivid, and the layering of the image after the color enhancement processing is improved.

In one of the embodiments, the image processing method further includes performing corresponding color enhancement processing on the image to be processed according to the current color mode and/or rendering intent of the display screen to generate a fourth enhanced image, and the fourth enhanced image and the second enhanced image The images are fused.

Wherein, the above-mentioned color enhancement processing can be realized by calling the preset color adjustment interface of the platform. Specifically, the preset color modes of the mobile phone platform include natural color, enhanced effect, saturated color and automatic adjustment. Preset rendering intents include Perceptually Constant, Relative Hue Matching, Absolute Hue Matching, and Saturation. Among them, the perceptually constant rendering intent can be used in the scene of photographic pictures, for example, the rendering intent of relative color matching can be used in the scene of rendering Logo graphics, and the rendering intent of absolute color matching can be used, for example, of simulating paper media In the scene, the saturation rendering intent can be commonly used in the scene of business diagrams and illustrations, for example. It can be understood that, the above specific methods of performing color enhancement processing and fusing two enhanced images based on the color mode and rendering intent are preset by the platform, and are not limited in this embodiment. It is understandable that the platform can adjust the color of the image to be processed based on the preset method. However, due to the platform's protection strategy for Gamma2.2 and the color gamut protection strategy, the platform can only make certain fine-tuning. Therefore, in this embodiment, a more flexible and accurate color enhancement effect can be realized through the second enhanced image generated in the foregoing embodiments.

Fig. 6 is a frame diagram of the internal structure of a display device in an embodiment. With reference to Fig. 6, the display device may include a software part and a hardware part, the hardware part includes a display screen for display, and the software part includes an application layer (APP), a Layer (Framework) and core layer (kernel). The framework layer can also be specifically divided into the Java part and the Native part. The Java part is used to connect with the application program, but the Java language itself cannot access and operate the bottom layer of the operating system. Therefore, the Native part can be set to interact with the bottom layer. Among them, the Java part can call the Native part through the Java native interface (Java NativeInterface, JNI).

Among them, in this embodiment, the application layer obtains the preference selection result carrying the user's enhanced preference information through interaction with the user, and obtains the target enhancement coefficient ratio that can represent the user's enhanced preference information through analysis, and obtains the The target enhancement factor ratio is passed to the database and is called the Strength value. In addition, other information such as SystemUI and Setting may also be stored in the database.

The framework layer can determine the change of the database information of the application layer through the framework monitoring, and obtain the corresponding SettingProvider key value and Strength intensity value when the database information changes. Among them, the SettingProvider key value is the flag bit of the button, which is used to identify which button of the mobile phone is pressed to trigger the subsequent logic of the software. After the above data is obtained, the data is transmitted in two ways.

Among them, one channel of data is transmitted through the Android HIDL interface. On the one hand, it reaches the core layer path through the Android HIDL interface to issue the largest IR-drop instruction to the display driver chip of the screen, and on the other hand, it reaches the basic effect path to realize the user's personality. Color enhancement. Among them, the 3DLut_ENH module is used to perform multiple steps, specifically including the aforementioned acquisition of the skin color area in the image to be processed, and adjusting the color attributes of the skin color area to protect the color of the skin color area. According to the tone distribution of the image to be processed, the The image is divided into multiple areas to be enhanced, and corresponding color enhancement processing is performed on each area to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed. The 3DLut_IRC module is used to compensate the image after color enhancement processing according to the average image level, so as to improve the transparency of the image by adjusting the degree of IR-drop. The 3DLut_ENIR module is used to fuse and solidify the effects of the 3DLut_ENH module and the 3DLut_IRC module. The 3DLut_CC module is used to fuse the first enhanced image and the second enhanced image according to the target enhancement coefficient ratio to generate a third enhanced image, wherein the first enhanced image refers to coloring the image to be processed according to the current preset color effect of the display screen The image generated by enhancement processing, the second enhanced image refers to an image generated by color enhancement processing based on the user's enhancement preference information. The other way of data is transmitted through the RenderIntent interface, and reaches SurfaceFlinger and mobile_color_mode to perform color fine-tuning according to the color mode and rendering intent. After the two channels of image data are processed, they are fused and transmitted to the Phone_color hardware at the core layer.

The Phone_color hardware at the core layer gets the data and writes it into the hardware color engine register of the display to realize the display at the hardware layer.

It should be understood that although the steps in the flow charts involved in the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flow charts involved in the above embodiments may include multiple steps or stages, and these steps or stages are not necessarily executed at the same time, but may be executed at different times, The execution order of these steps or stages is not necessarily performed sequentially, but may be executed in turn or alternately with other steps or at least a part of steps or stages in other steps.

Based on the same inventive concept, an embodiment of the present application further provides an image processing device for implementing the above-mentioned image processing method. The solution to the problem provided by the device is similar to the implementation described in the above method, so the specific limitations in one or more embodiments of the image processing device provided below can refer to the above definition of the image processing method, I won't repeat them here. Wherein, the image processing device includes a preference acquisition module, an area division module and an enhancement processing module.

The preference obtaining module is used to obtain the user's enhanced preference information. The area division module is used to obtain the image to be processed, and divide the image to be processed into multiple areas to be enhanced according to the tone distribution of the image to be processed. The enhancement processing module is used to perform corresponding color enhancement processing on each area to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.

Each module in the above-mentioned image processing device may be fully or partially realized by software, hardware or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, and can also be stored in the memory of the electronic device in the form of software, so that the processor can invoke and execute the corresponding operations of the above-mentioned modules.

The embodiment of the present application also provides a display device, including a connected display screen and a processor. The processor is used to obtain the enhancement preference information of the user; obtain the image to be processed, divide the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed; perform corresponding color enhancement processing on each region to be enhanced according to the enhancement preference information , to adjust the color attributes of the image to be processed; and send the image after adjusting the color attributes to the display screen for display.

In one embodiment, an electronic device is provided, and the electronic device may be a display device. FIG. 7 is an internal structure diagram of the electronic device in one embodiment. The electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Wherein, the processor of the electronic device is used to provide calculation and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the electronic device is used for wired or wireless communication with an external display device, and the wireless method can be realized through WIFI, mobile cellular network, NFC (Near Field Communication) or other technologies. When the computer program is executed by a processor, an image processing method is realized. The display screen of the electronic device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device may be a touch layer covered on the display screen, or a button, a trackball or a touch pad provided on the housing of the electronic device , and can also be an external keyboard, touchpad, or mouse.

Those skilled in the art can understand that the structure shown in FIG. 7 is only a block diagram of a partial structure related to the solution of this application, and does not constitute a limitation on the electronic equipment to which the solution of this application is applied. The specific electronic equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment, an electronic device is provided, including a memory and a processor, where a computer program is stored in the memory, and the processor implements the steps in the foregoing method embodiments when executing the computer program.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the foregoing method embodiments are implemented.

In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the foregoing method embodiments are implemented.

Those of ordinary skill in the art can understand that realizing all or part of the processes in the methods of the above embodiments can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a non-volatile computer-readable storage medium , when the computer program is executed, it may include the procedures of the embodiments of the above-mentioned methods. Wherein, any reference to storage, database or other media used in the various embodiments provided in the present application may include at least one of non-volatile and volatile storage. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive variable memory (ReRAM), magnetic variable memory (Magnetoresistive Random Access Memory, MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (Phase Change Memory, PCM), graphene memory, etc. The volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a blockchain-based distributed database, etc., but is not limited thereto. The processors involved in the various embodiments provided by this application can be general-purpose processors, central processing units, image processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., and are not limited to this.

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above examples only express several implementation modes of the present application, and its description is relatively specific and detailed, but it should not be interpreted as limiting the patent scope of the present application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be determined by the appended claims.

Claims (20)

1. An image processing method, the method comprising:

   Obtain the user's enhanced preference information;

   Acquiring an image to be processed, dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed;

   Perform corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.
2. The image processing method according to claim 1, said obtaining enhanced preference information of the user comprises:

   Generate a candidate image set, the candidate image set includes a plurality of images, and the color enhancement processing parameters corresponding to the multiple images in the same candidate image set are different;

   Obtaining a user's preference selection result for multiple images in each of the candidate image sets, and obtaining the enhanced preference information according to the preference selection result.
3. According to the image processing method according to claim 2, the number of the candidate image sets is multiple, wherein the color enhancement processing parameters corresponding to a plurality of images in the n+1th candidate image set are determined by the nth candidate image set The result of preference selection is determined, and n is a positive integer.
4. According to the image processing method according to claim 2, the number of the candidate image sets is two, and the generation of the candidate image sets includes:

   generating a first set of candidate images according to the first initial image of blue-green tone and first parameters;

   A second set of candidate images is generated according to the second initial image in red, green, and blue tones and the second parameters.
5. The image processing method according to claim 4, said generating a second candidate image set according to the second initial image of red, green and blue tone and second parameters, comprising:

   determining the second parameter of the color enhancement process according to a user's preference selection result of a plurality of images in the first candidate image set;

   The second candidate image set is generated according to the determined second parameter and the second initial image of the red-green-blue tone.
6. According to the image processing method according to claim 2, the plurality of images in the candidate image set are respectively configured with a plurality of corresponding image enhancement coefficients in one-to-one correspondence, and the enhancement preference information is acquired according to the preference selection result ,include:

   Respectively acquire candidate enhancement coefficients corresponding to each of the candidate image sets, where the candidate enhancement coefficients are the image enhancement coefficients corresponding to an image selected by the user from the candidate image sets;

   Obtaining a target enhancement coefficient as the enhancement preference information according to the plurality of candidate enhancement coefficients.
7. The image processing method according to claim 6, said obtaining enhanced preference information of the user, further comprising:

   If a coefficient adjustment signal acting on a specified trigger area of the interface is received, the target enhancement coefficient is updated according to the coefficient adjustment signal.
8. According to the image processing method according to claim 6, performing corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information, comprising:

   Acquire the color correction matrix corresponding to the target enhancement coefficient, each of the color correction matrices corresponds to at least one of the regions to be enhanced;

   Perform color enhancement processing according to the color correction matrix corresponding to each of the regions to be enhanced.
9. The image processing method according to claim 8, said acquiring the color correction matrix corresponding to the target enhancement coefficient comprises:

   According to the target enhancement coefficient, different or the same color correction matrix is selected for different areas to be enhanced.
10. According to the image processing method according to claim 8, said dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed comprises:

    dividing the image to be processed into a plurality of regions to be enhanced and at least one transition region according to the tone distribution of the image to be processed;

    The image processing method also includes:

    Smoothing the color attributes of the transition region according to the color attributes of the plurality of regions to be enhanced after color enhancement processing.
11. The image processing method according to claim 6, further comprising:

    performing color enhancement processing on the image to be processed according to the current preset color effect of the display screen to generate a first enhanced image;

    Fusing the first enhanced image and the second enhanced image according to the target enhancement coefficient to generate a third enhanced image, the second enhanced image corresponds to each of the regions to be enhanced according to the enhancement preference information The resulting image is color enhanced.
12. The image processing method according to claim 6, further comprising:

    When the target enhancement coefficient is equal to the coefficient threshold, obtain the target color gamut supported by the display screen;

    If the target color gamut is larger than the color gamut of the image after color enhancement processing, then perform color gamut expansion on the image after color enhancement processing.
13. The image processing method according to claim 1, before dividing the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed, further comprising:

    Acquiring the skin color area in the image to be processed;

    Adjusting the color attribute of the skin color area to protect the color of the skin color area.
14. The image processing method according to claim 13, before acquiring the skin color area in the image to be processed, further comprising: converting the image to be processed from RGB color space to a target color space, and the target color space is HSI color space or HSV color space;

    After the adjusting the color attribute of the skin color area, the method further includes: converting the image after adjusting the color attribute of the skin color area from the target color space to the RGB color space.
15. The image processing method according to claim 1, further comprising:

    Obtaining the average image level of the image after color enhancement processing;

    The brightness of each color channel is adjusted respectively according to the average image level, so as to adjust the contrast of the image after color enhancement processing.
16. The image processing method according to claim 1, further comprising:

    Perform corresponding color enhancement processing on the image to be processed according to the current color mode and/or rendering intent of the display screen to generate a fourth enhanced image;

    Fusing the fourth enhanced image and the second enhanced image to generate a target display image, the second enhanced image is generated by performing corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information image.
17. An image processing device, the device comprising:

    A preference acquisition module, configured to acquire enhanced preference information of the user;

    An area division module, configured to acquire an image to be processed, and divide the image to be processed into a plurality of areas to be enhanced according to the tone distribution of the image to be processed;

    An enhancement processing module, configured to perform corresponding color enhancement processing on each of the regions to be enhanced according to the enhancement preference information, so as to adjust the color attributes of the image to be processed.
18. A display device comprising:

    display screen;

    A processor, connected to the display screen, configured to acquire user enhancement preference information; acquire an image to be processed, and divide the image to be processed into a plurality of regions to be enhanced according to the tone distribution of the image to be processed; The enhancement preference information performs corresponding color enhancement processing on each of the regions to be enhanced, so as to adjust the color attribute of the image to be processed; and sends the image with the adjusted color attribute to the display screen for display.
19. An electronic device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 16 when executing the computer program.
20. A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are realized.

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