Image processing method and apparatus, and electronic device and storage medium

Abstract

An image processing method and apparatus, and an electronic device (1000) and a storage medium (1100). The image processing method is applied to a display screen, and comprises: on the basis of a time-window weight and historical brightness images, recording historical heat time accumulation information of a display screen, so as to obtain the current heat time accumulation image of the display screen, wherein the time-window weight is used for describing a weight coefficient of the current impact of the historical brightness images in a time window up to the present moment on the temperature of the display screen (S100); and on the basis of the heat time accumulation image, compensating a first image frame among a plurality of image frames to be displayed on the display screen, so as to obtain a first compensated image frame after compensation, wherein the first compensated image frame is used for driving the display screen to present the first image frame (S200). In the image processing method, an image frame displayed on a display screen is compensated, thereby preventing the problem of afterimage caused by differences in LED luminous efficiencies and thermal effects resulting from prolonged image display.

Description

Image processing method and device, electronic device and storage medium Technical Field

[0001] Embodiments of the present disclosure relate to an image processing method and apparatus, an electronic device, and a storage medium. Background Art

[0002] In the field of image display, mini light-emitting diode (MLED) displays are becoming increasingly popular. MLED displays offer higher resolution than LED displays, with MLED chip sizes typically ranging from 50 to 200 μm. This results in more detailed displays and lower power consumption. MLED chips also offer a long display life and low cost, making them popular with users. With the rapid development of MLED display technology, MLED display products have begun to be used in ultra-large, high-definition displays for commercial applications such as surveillance and command, high-definition broadcasting, high-end cinemas, medical diagnostics, advertising displays, conference and exhibition, office displays, and virtual reality.

[0003] Summary of the Invention

[0004] At least one embodiment of the present disclosure provides an image processing method for a display screen, the image processing method comprising: recording historical thermal time accumulation information of the display screen based on a time window weight and a historical brightness image, and obtaining a current thermal time accumulation image of the display screen, wherein the time window weight is used to describe a weight coefficient of the current influence of the historical brightness image in the time window up to the current time on the temperature of the display screen; compensating a first image frame of multiple image frames to be displayed on the display screen according to the thermal time accumulation image, and obtaining a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

[0005] For example, in the image processing method provided in at least one embodiment of the present disclosure, the historical thermal time accumulation information of the display screen is recorded based on the time window weight and the historical brightness image to obtain the current thermal time accumulation image of the display screen, including: using the time window weight to perform weighted fusion on the first number of historical brightness images accumulated in the cache pool to obtain the thermal time accumulation image.

[0006] For example, in the image processing method provided in at least one embodiment of the present disclosure, after obtaining the current thermal time accumulation image of the display screen, it also includes: updating the cache pool based on the first image frame to obtain a thermal time accumulation image for at least another image frame after the first image frame.

[0007] For example, in the image processing method provided in at least one embodiment of the present disclosure, the updating of the cache pool based on the first image frame includes: performing grayscale processing on the first image frame to obtain a first grayscale image corresponding to the first image frame; converting the first grayscale image into a first brightness image corresponding to the first image frame according to a grayscale-brightness mapping relationship; adding the first brightness image corresponding to the first image frame to the cache pool, and in response to the number of historical brightness images in the cache pool reaching a preset number threshold before the first brightness image corresponding to the first image frame is added, removing the historical brightness image in the cache pool that is farthest from the current moment.

[0008] For example, in the image processing method provided in at least one embodiment of the present disclosure, the grayscale processing of the first image frame to obtain the first grayscale image corresponding to the first image frame includes: obtaining the temperature rise curve of the display screen when the temperature fluctuation value reaches a preset range when displaying red, blue, and green images, and obtaining the proportional coefficient of the grayscale processing based on the temperature rise curves in the three cases; grayscale processing of the first image frame according to the proportional coefficient to obtain the first grayscale image corresponding to the first image frame.

[0009] For example, in the image processing method provided by at least one embodiment of the present disclosure, before recording the historical thermal time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current thermal time accumulation image of the display screen, it also includes: obtaining the temperature rise curve from the time when the display screen displays a full white screen to the state where the temperature fluctuation value reaches a preset range; and obtaining the time window weight based on the temperature rise curve.

[0010] For example, in the image processing method provided in at least one embodiment of the present disclosure, compensating the first image frame among the multiple image frames to be displayed on the display screen according to the thermal time accumulation image to obtain the compensated first compensated image frame includes: subtracting the weighted thermal time accumulation image from the three channel components in the first image frame to obtain the first compensated image frame.

[0011] For example, in the image processing method provided in at least one embodiment of the present disclosure, the first grayscale image is converted into a first brightness image corresponding to the first image frame according to the grayscale-brightness mapping relationship, including: dividing the first grayscale image into multiple first areas of the same size, and the multiple first areas correspond to multiple first-area grayscale images; dividing each first-area grayscale image into multiple second areas of the same size; for each first-area grayscale image, respectively calculating the grayscale mean of the grayscale image pixels in each second area to obtain multiple second-area grayscale images, converting the multiple second-area grayscale images into multiple second-area brightness images according to the grayscale-brightness mapping relationship, calculating the brightness mean in the corresponding second area for each of the multiple second-area brightness images, to obtain multiple unit mean brightness images corresponding to the multiple second-area brightness images.

[0012] For example, in the image processing method provided by at least one embodiment of the present disclosure, after obtaining multiple unit mean brightness images corresponding to the multiple second area brightness images, converting the first grayscale image into a first brightness image corresponding to the first image frame according to the grayscale-brightness mapping relationship also includes: performing a boundary search on the mean brightness image to obtain a boundary search map, wherein the mean brightness image includes all unit mean brightness images; superimposing the boundary search map with the second brightness image to obtain an intermediate brightness image affected by the superimposed boundary, wherein the second brightness image includes all second area brightness images; normalizing the intermediate brightness image affected by the superimposed boundary to obtain a normalized brightness image as the first brightness image.

[0013] For example, in the image processing method provided in at least one embodiment of the present disclosure, the boundary search is performed on the mean brightness image to obtain a boundary search map, including: searching the boundary area of ​​the mean brightness image in multiple directions respectively, assigning values ​​to the searched areas according to a boundary search lookup table to obtain multiple sub-boundary search maps; and superimposing the multiple sub-boundary search maps to obtain the boundary search map.

[0014] For example, in the image processing method provided in at least one embodiment of the present disclosure, the display screen is a spliced ​​screen including multiple sub-display screens. The image processing method, after recording the historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current heat time accumulation image of the display screen, further includes: performing inter-sub-display screen diffusion filtering on the heat time accumulation image to obtain an inter-sub-display screen heat diffusion compensation map.

[0015] For example, in the image processing method provided in at least one embodiment of the present disclosure, performing inter-sub-display diffusion filtering on the heat time accumulation image to obtain the inter-sub-display heat diffusion compensation map includes: collecting multiple temperature image data of multiple different splicing screen display patterns, merging and normalizing the multiple temperature image data to obtain an inter-screen influence coefficient matrix; and performing inter-sub-display diffusion filtering on the heat time accumulation image using the inter-screen influence coefficient matrix to obtain the inter-sub-display heat diffusion compensation map.

[0016] For example, in the image processing method provided in at least one embodiment of the present disclosure, the display screen includes at least one sub-display screen. After recording the historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current heat time accumulation image of the display screen, the image processing method further includes: performing diffusion filtering within the at least one sub-display screen on the heat time accumulation image to obtain a heat diffusion compensation map within the at least one sub-display screen.

[0017] For example, in the image processing method provided in at least one embodiment of the present disclosure, performing diffusion filtering within the at least one sub-display screen on the comprehensive historical influence map to obtain the at least one sub-display screen heat diffusion compensation map includes: performing diffusion filtering within the at least one sub-display screen on the heat time accumulation image using a Gaussian filter kernel to obtain the at least one sub-display screen heat diffusion compensation map.

[0018] For example, in the image processing method provided in at least one embodiment of the present disclosure, after the first image frame is grayscaled to obtain the first grayscale image corresponding to the first image frame, it also includes: obtaining a grayscale-maximum compensation value lookup table; obtaining the maximum compensation value of each pixel in the first grayscale image according to the grayscale-maximum compensation value lookup table to obtain a maximum compensation value map.

[0019] For example, in the image processing method provided in at least one embodiment of the present disclosure, the grayscale-maximum compensation value lookup table is obtained, including: obtaining the brightness of different grayscales at the lowest temperature and the brightness at the highest temperature; taking the difference between the grayscale value at the lowest temperature and the grayscale value at the highest temperature under the same brightness as the maximum compensation value of the grayscale value at the highest temperature, and constructing the grayscale-maximum compensation value lookup table.

[0020] For example, in the image processing method provided in at least one embodiment of the present disclosure, compensating the first image frame according to the heat-time accumulation image to obtain a compensated first compensated image frame includes: processing the maximum compensation value map based on the intra-screen thermal diffusion compensation map and / or the inter-screen thermal diffusion compensation map to obtain a composite compensation map; and subtracting the weighted composite compensation map from the three channel components in the first image frame to obtain the first compensated image frame.

[0021] At least one embodiment of the present disclosure provides an image processing device for a display screen, the image processing device comprising: a time accumulation module, configured to record historical thermal time accumulation information of the display screen based on a time window weight and a historical brightness image, to obtain a current thermal time accumulation image of the display screen, wherein the time window weight is used to describe a weight coefficient of the current influence of the historical brightness image in the time window up to the current time on the temperature of the display screen; a compensation module, configured to compensate a first image frame of multiple image frames to be displayed on the display screen according to the thermal time accumulation image, to obtain a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

[0022] At least one embodiment of the present disclosure provides an image processing device, which includes: at least one processor; at least one memory, including one or more computer program modules; wherein the one or more computer program modules are stored in the at least one memory and are configured to be executed by the at least one processor, and the one or more computer program modules include instructions for executing the image processing method provided by at least one embodiment of the present disclosure.

[0023] At least one embodiment of the present disclosure provides an electronic device, which includes: the image processing device provided by at least one embodiment of the present disclosure.

[0024] For example, the electronic device provided in at least one embodiment of the present disclosure further includes: the display screen; and a timing controller configured to receive the first compensated image frame generated by the image processing device to drive the display screen to present the first image frame.

[0025] For example, in the electronic device provided in at least one embodiment of the present disclosure, the display screen is a mini light emitting diode display screen.

[0026] At least one embodiment of the present disclosure provides a non-transitory readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by at least one processor, perform the image processing method provided by at least one embodiment of the present disclosure.

[0027] At least one embodiment of the present disclosure provides a computer program product, including a computer program / instruction, wherein when the computer program / instruction is executed by at least one processor, the image processing method provided by at least one embodiment of the present disclosure is performed. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present disclosure, rather than limiting the present disclosure.

[0029] FIG1 is a flowchart of an image processing method provided by at least one embodiment of the present disclosure;

[0030] FIG2 is a schematic diagram of obtaining a first brightness image according to at least one embodiment of the present disclosure;

[0031] FIG3 is a schematic diagram of obtaining a time-accumulated heat image according to at least one embodiment of the present disclosure;

[0032] FIG4 is a schematic diagram of a boundary search method provided by at least one embodiment of the present disclosure;

[0033] FIG5 is a schematic diagram of intra-screen diffusion filtering according to at least one embodiment of the present disclosure;

[0034] FIG6 is a schematic diagram of inter-screen diffusion filtering provided by at least one embodiment of the present disclosure;

[0035] FIG7 is a flowchart of an image processing method provided by at least one embodiment of the present disclosure;

[0036] FIG8 is a schematic block diagram of an image processing device provided by at least one embodiment of the present disclosure;

[0037] FIG9 is a schematic block diagram of another image processing device provided by at least one embodiment of the present disclosure;

[0038] FIG10 is a schematic block diagram of another image processing device provided by at least one embodiment of the present disclosure;

[0039] FIG11 is a schematic block diagram of an electronic device provided by at least one embodiment of the present disclosure; and

[0040] FIG12 is a schematic block diagram of a non-transitory readable storage medium provided by at least one embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0042] Unless otherwise defined, the technical or scientific terms used in this disclosure should have the usual meanings understood by persons of ordinary skill in the field to which this disclosure belongs. The words "first", "second" and similar terms used in this disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "include" or "comprise" mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0043] The present disclosure is described below using several specific embodiments. To keep the following description of the embodiments of the present disclosure clear and concise, detailed descriptions of known functions and components may be omitted. When any component of an embodiment of the present disclosure appears in more than one drawing, the component is represented by the same or similar reference numeral in each drawing.

[0044] The inventors of the present disclosure noticed that when different grayscales are displayed in different areas of a display screen, due to the different heat accumulation in different areas of the display screen, when the display screen is an MLED display screen, the MLED luminous efficiency in different areas of the display screen is different. For example, in areas with more heat accumulation, the MLED luminous efficiency is reduced, and in areas with less heat accumulation, the MLED luminous efficiency is still relatively high. After the display screen displays a certain image for a long time, when the entire display screen is switched to the same grayscale display, afterimages are likely to appear in areas with more heat accumulation and low MLED luminous efficiency, which ultimately leads to uneven display of the picture when the entire display screen is switched to the same grayscale display, reducing the display effect and affecting the user experience.

[0045] At least one embodiment of the present disclosure provides an image processing method, which is used for a display screen, and the image processing method includes: recording historical thermal time accumulation information of the display screen based on a time window weight and a historical brightness image, and obtaining a current thermal time accumulation image of the display screen, wherein the time window weight is used to describe the weight coefficient of the current influence of the historical brightness image in the time window up to the current time on the temperature of the display screen; compensating a first image frame of multiple image frames to be displayed on the display screen according to the thermal time accumulation image, and obtaining a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

[0046] The image processing method provided by at least one embodiment of the present disclosure records the historical thermal time accumulation information of the display screen based on the time window weight and the historical brightness image, obtains the current thermal time accumulation image of the display screen, and compensates the first image frame displayed on the display screen according to the thermal time accumulation image, and adjusts the image chromaticity of the area with high luminous efficiency of the light-emitting element in the display screen to be consistent with the chromaticity of the area with low luminous efficiency, thereby eliminating the afterimage. Even after the display screen displays a certain image for a long time, when the entire display screen is switched to the same grayscale display, it can still ensure that the display screen displays the picture uniformly, thereby improving the display effect and user experience.

[0047] In the embodiments of the present disclosure, the light-emitting elements in the display screen may be, for example, MLEDs, micro-LEDs, LEDs, etc. The present disclosure does not impose any restrictions on the specific circuit structures (such as the connection method and quantity of transistors and capacitors), preparation materials (such as gallium nitride, etc.), preparation processes (such as semiconductor preparation processes, etc.), and packaging methods of these LEDs.

[0048] The image processing method provided by the present disclosure is described below in a non-restrictive manner through multiple embodiments and examples. As described below, different features in these specific examples or embodiments can be combined with each other without conflicting with each other to obtain new examples or embodiments, and these new examples or embodiments also fall within the scope of protection of the present disclosure.

[0049] FIG1 is a flow chart of an image processing method provided by at least one embodiment of the present disclosure. The image processing method is applied to a display screen that receives image pixel data and displays the image according to the image pixel data. The display screen can display dynamic images (e.g., videos) or static images (e.g., photos) during the display process, and refreshes image frames during the display process; these image frames can be color or black and white.

[0050] As shown in FIG1 , the image processing method provided in this embodiment of the present disclosure includes the following steps S100 to S200:

[0051] Step S100: Record the historical thermal time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current thermal time accumulation image of the display screen, wherein the time window weight is used to describe the weight coefficient of the current influence of the historical brightness image in the time window up to the current time window on the temperature of the display screen.

[0052] For example, the historical brightness image includes the brightness image corresponding to the image frame before the current moment. For example, brightness images (historical brightness images) over a period of time in the past (e.g., 10 minutes, 20 minutes, or half an hour, etc.) are saved, and the above brightness images are weightedly fused using the time window weight to obtain a historical thermal time accumulation image of the display screen. For example, the time window weight is used to describe the weight coefficient of the current impact of the historical brightness image in the time window up to the current time on the temperature of the display screen. It can be obtained based on experiments or simulations, or it can be obtained by processing the measured temperature rise curve. This is not limited by the present disclosure.

[0053] Step S200: compensating a first image frame among a plurality of image frames to be displayed on a display screen according to a heat time accumulation image to obtain a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

[0054] For example, the thermal time-accumulated image records the compensation value that needs to be increased or decreased for each pixel in the first image frame. Based on the compensation value, the original first image frame is processed pixel by pixel to generate a first compensated image frame. For example, the obtained first compensated image frame is transmitted to a controller of the display screen (such as a timing controller), and the controller drives each pixel unit of the display screen according to the compensated value. Therefore, during actual presentation, the image quality consistency and accuracy can be maintained even when the display screen is in operation for a long time.

[0055] For example, the above method step S100 includes the following steps S110-S120:

[0056] Step S110: performing weighted fusion on a first number of historical brightness images accumulated in the buffer pool using a time window weight to obtain a thermal time accumulation image.

[0057] For example, the cache pool stores multiple (historical) brightness images obtained within a period of time in the past (for example, within a predetermined time before the current image frame, i.e., the first image frame), and the above historical brightness images are weightedly fused using the time window weight to obtain the current thermal time accumulation image of the display screen.

[0058] It should be noted that the above time length can be any value and is not limited by the present disclosure. For example, the time length can be the time from when the display screen is turned on to when the temperature fluctuation value reaches a state within a preset range when the display screen displays a completely white screen. For example, the time length can be half an hour. When one frame is collected per second (i.e., the sampling frequency is 1), the corresponding first number is 1800.

[0059] For example, taking the time length as half an hour and the first number as 1800 as an example, the cache pool stores 1800 frames of historical brightness images accumulated in the past half hour.

[0060] For example, when the display screen is turned on, since there is no historical data, the buffer pool can be filled with 1800 frames of all-white or all-black images to serve as an initial baseline. Step S120: Update the buffer pool based on the first image frame to obtain a thermal time accumulation image for at least another image frame after the first image frame.

[0061] For example, the other image frame may be an image frame to be displayed immediately after the first image frame in time, or an image frame to be displayed after a predetermined time period (for example, 0.1 second or 1 second, etc.). The embodiments of the present disclosure do not limit this, and thus the compensation operation of the other image frame takes into account the influence of the parameters of the display process of the previous first image frame.

[0062] For example, the above method step S120 includes the following steps S101-S103:

[0063] Step S101: performing grayscale processing on a first image frame to obtain a first grayscale image corresponding to the first image frame.

[0064] The multiple image frames displayed above can be multiple image frames displayed continuously in the video, or can be multiple image frames for realizing repeated display of static images; here, "first image frame" is used to refer to the image frame that is the current description object (not necessarily the first image frame of the multiple image frames sorted in time), which can be any image frame among the above multiple image frames.

[0065] For example, the pixel data for each pixel in the first image frame can be 8-bit unsigned data with a value range of [0, 255], which can provide sufficient accuracy to express common image pixel value information. It should be noted that the embodiments of the present disclosure are not limited to the above-mentioned specific data size and format. The pixel data of the first image frame can use unsigned or signed data of different bit widths, such as 10 bits, 12 bits, etc., and the appropriate dynamic range can be selected according to the actual application scenario and requirements. The methods and steps described below are also applicable to data of other bit widths and types. It is only necessary to adjust the calculation and processing methods accordingly. The following description will not be repeated. For example, in the case of color images, grayscale processing mainly converts the color information of each pixel in the original color image (usually including the three color channels of red, green, and blue (RGB)) into a single grayscale value; in the case of black and white images, grayscale processing can include converting the grayscale information of each pixel in the original black and white image into a grayscale value corresponding to the above-mentioned display screen. For example, the grayscale value can be calculated using a specific conversion function, such as ITU-R 601, ITU-R 709, or the average method. For example, the proportional coefficient of the grayscale processing can also be obtained based on the three-channel temperature rise curve of the display screen. The temperature rise curve can be an empirical temperature rise curve obtained through experiments or simulations, or a measured temperature rise curve. This disclosure does not limit this.

[0066] Step S102: converting the first grayscale image into a first brightness image corresponding to the first image frame according to the grayscale-brightness mapping relationship.

[0067] For example, in a digital image or video system, grayscale is a continuous range that represents different levels from the darkest (black) to the brightest (white), and the value can range from 0 to 255 (taking 8-bit bit width as an example). There is a certain conversion relationship between grayscale and actual display brightness, that is, different grayscale values ​​correspond to different screen brightness outputs. This conversion is not linear, but follows a specific function curve to ensure that the human eye's perception of different brightness levels is as close as possible to the visual experience in the natural environment. For example, a gamma curve can be used as a specific mathematical model to describe the above-mentioned nonlinear relationship, or other models can be used, and the present disclosure does not limit this.

[0068] Step S103: Add the first brightness image corresponding to the first image frame to the cache pool, and in response to the number of historical brightness images in the cache pool reaching a preset number threshold before the first brightness image corresponding to the first image frame is added, remove the historical brightness image frame farthest from the current moment in the cache pool.

[0069] For example, taking the time length as half an hour and the first number as 1800 as an example, the cache pool stores 1800 frames of historical brightness images accumulated in the past half hour, and each frame of historical brightness image is obtained by processing another image frame before the first image frame through the above steps S101-S102.

[0070] For example, the current first image frame is captured every 1 second, and a first brightness image is obtained after processing through the above steps S101-S102. When the first brightness image is added to the buffer pool, if the number of brightness images in the buffer pool has reached 1800 before the first brightness image corresponding to the first image frame is added, the historical brightness image frame farthest from the current moment in the buffer pool is removed to keep the buffer pool always containing the data of the most recent half hour. The data in the current buffer pool is used to generate a thermal time accumulation image of at least another image frame after the first image frame. It should be noted that the embodiments of the present disclosure do not impose any restrictions on the above-mentioned preset number threshold, and can be adjusted according to actual conditions; for example, the preset number threshold can be fixed (i.e., cannot be modified) in the corresponding processing device, or can be flexibly set or modified, for example, by means of a writable memory (e.g., a register). For example, each pixel of the image frame includes RGB sub-pixels, and each pixel of the display screen also includes red, blue, and green light-emitting elements (such as red MLED, blue MLED, and green MLED) for the RGB sub-pixels, respectively. Correspondingly, step S101 of the above method includes the following steps S1011-S1012:

[0071] Step S1011: obtaining temperature rise curves when the display screen displays red, blue, and green images and the temperature fluctuation value reaches a preset range, and obtaining a grayscale processing proportional coefficient according to the temperature rise curves in the three cases.

[0072] Step S1012: grayscale the first image frame according to the proportional coefficient to obtain a first grayscale image corresponding to the first image frame.

[0073] The three images of full red, full blue and full green respectively correspond to the situations where only all red light, only all blue light and only all green light emitting elements in the display screen are turned on, thereby avoiding the situation where the three light emitting elements affect each other.

[0074] FIG2 is a schematic diagram of acquiring a first brightness image provided by at least one embodiment of the present disclosure.

[0075] For example, as shown in Figure 2, by measuring the temperature rise curves (R channel, B channel, G channel temperature rise curves) of the display screen when the temperature fluctuation value reaches the preset range after a certain period of time when the display screen displays three images of full red, full blue, and full green, the temperature rise ratio of the RGB three channels in the display screen is obtained as T R :T G :TB =0.596577:0.13018:0.27324, and grayscale the first image frame using this ratio as the proportional coefficient for grayscale processing. For example, the temperature fluctuation value referred to herein as falling within a preset range may mean that the temperature itself remains unchanged, or that the temperature changes steadily over time, exhibiting only a small temperature fluctuation. This is not limited in the present embodiment. For example, the present embodiment does not limit the preset range of the temperature fluctuation value.

[0076] It should be noted that the above-mentioned proportional coefficient is related to the characteristics of the display screen. Different display screens will have different proportional coefficients. The above-mentioned three-channel temperature rise ratio is only an example and does not constitute a limitation to the present disclosure.

[0077] For example, the first grayscale image I is calculated according to the scale factor of the grayscale processing. Gray The specific formula is as follows: Gray =T R ×I R +T G ×I G +T B ×I B =0.596577×I R +0.13018×I G +0.27324×I B

[0078] Among them, I R , I G , I B They are the values ​​of the RGB channels in the first image frame respectively.

[0079] For example, the first image frame is 8-bit unsigned data with a value range of [0, 255], and the scale factor used for adjustment in the above formula is a floating-point number, and the scale factor needs to be fixed-point processed. Fixed-point processing refers to the process of converting a floating-point number into a fixed-point number. For example, first multiply the floating-point number by a suitable scaling factor and then round it off. This is because most hardware and underlying operations prefer to process integers rather than floating-point numbers, especially in scenarios such as embedded systems, digital signal processors (DSPs) or display driver circuits. In order to improve computing efficiency and reduce resource consumption, fixed-point representation and calculation are usually used. For example, multiply the scale factor matrix [0.596577, 0.13018, 0.243243] by a scaling factor (for example, 2 20 ), and get the fixed-point proportional coefficient matrix [625556,136503,286516].

[0080] For example, the first grayscale image I is calculated according to the scale coefficient after the fixed point processing. GrayThe specific formula is as follows: Gray =625556×I R +136503×I G +286516×I B

[0081] For example, after the calculation is completed I Gray The data width is 28 bits, which is shifted and rounded to obtain an 8-bit first grayscale image.

[0082] For example, in step S102, the grayscale-brightness mapping relationship can be represented by a grayscale-brightness curve as shown in FIG2 , and can be fitted by the following formula: Y=G b

[0083] Where G is the grayscale value of the pixel, Y is the brightness value of the pixel, and b is the mapping coefficient. For example, b = 1.8. Since b is a floating-point number, in one example, in order to avoid direct floating-point operations, a lookup table can be used to perform fixed-point calculations.

[0084] For example, first normalize the 8-bit unsigned grayscale value G from the range [0,255] to [0,1], and then substitute it into the above formula to calculate 256 different Y values, forming a continuous brightness value Y sequence. Multiply the continuous brightness value Y sequence obtained above by a suitable scaling factor (for example, 2 10 ), and then round it off and convert it into a 10-bit fixed-point format, forming a grayscale-brightness value lookup table with a length of 256, as shown in Table 1:

[0085] Table 1: Grayscale-brightness value lookup table

[0086] It should be noted that the grayscale-brightness value lookup table can also be adjusted according to actual needs, and the present disclosure does not impose any limitation on this.

[0087] For example, all grayscale values ​​in the first grayscale image are mapped using a grayscale-brightness value lookup table to convert the first brightness image. For example, the data bit width of the first brightness image is 10 bits.

[0088] For example, before step S100, the image processing method in the above example further includes: obtaining a temperature rise curve from when the display screen displays a full white screen to when the temperature fluctuation value reaches a preset range; and obtaining a time window weight based on the temperature rise curve.

[0089] FIG3 is a schematic diagram of obtaining a time-accumulated heat image according to at least one embodiment of the present disclosure.

[0090] For example, as shown in FIG3 , the time window weight is obtained by sampling the temperature rise curve from the time the display screen displays a full white screen to the time the temperature fluctuation value reaches a preset range. For example, as shown in FIG3 , the temperature rise curve is processed to obtain the time window weight corresponding to 1800 frames, and the time window weight is a 1×1800 vector. For example, data processing includes at least one of a mirror operation, a negation operation, and a normalization operation. For example, the temperature fluctuation value referred to here as reaching a preset range may mean that the temperature itself remains unchanged, or that the temperature changes over time and only exhibits temperature fluctuations within a small range. The embodiment of the present disclosure does not limit the size of the range within the preset range or the calculation method.

[0091] For example, as shown in Figure 3, the weight value on the far right of the time window weight represents the weight value of the frame closest to the current time. The weight value of the approximately 300 frames closest to the current time is significantly higher than the weight value of other earlier historical frames. This means that when estimating temperature-related compensation, the data closer to the current time contributes more to the current compensation value.

[0092] For example, in order to process these weights efficiently in hardware or algorithms, the time window weights in the range [0,1] need to be multiplied by a scaling factor (e.g., 2 18 ) is converted to a fixed point to obtain the time window weight after fixed point conversion.

[0093] For example, all historical brightness images in the buffer pool are multiplied and accumulated by the fixed-point time window weights to obtain a fixed-point thermal time accumulation image. For example, the fixed-point thermal time accumulation image is shifted and rounded to obtain a 10-bit thermal time accumulation image.

[0094] In the process of obtaining the above-mentioned thermal time accumulation image, a dynamic weighting strategy with strong real-time performance is realized by using the time window weight to perform weighted fusion on the historical accumulated brightness image.

[0095] For example, in step S200 , the weighted thermal time accumulation image is subtracted from the three channel components in the first image frame to obtain a first compensated image frame.

[0096] For example, after obtaining the thermal time accumulation image, the first image frame can be compensated by performing pixel-level subtraction operations on the three channel components of the first image frame and the weighted thermal time accumulation image. For the three independent color channels of RGB, the compensation coefficients are different. The specific calculation formula after compensation of each channel is as follows: C_R =I R -C R ×C w I C_G =IG -C G ×C w I C_B =I B -C B ×C w

[0097] Among them, C w is the thermal time accumulation image, I R , I G , I B are the values ​​of the RGB channels in the first image frame, I C_R , I C_G , I C_B are the values ​​after compensation of RGB three channels, C R , C G , C B They are the compensation coefficients corresponding to the RGB three channels, and the RGB three channel values ​​after compensation are I C_R , I C_G and I C_B The first image frame is integrated into an image as the output result after the final compensation processing of the current first image frame, that is, the first compensated image frame.

[0098] For example, in some examples, step 102 includes steps S1021-S1025.

[0099] Step S1021: dividing the first grayscale image into a plurality of first regions of the same size, wherein the plurality of first regions correspond to a plurality of first region grayscale images.

[0100] Step S1022: Divide each first-region grayscale image into a plurality of second regions of the same size.

[0101] Step S1023: for each first region grayscale image, calculate the grayscale mean of the grayscale image pixels in each second region to obtain a plurality of second region grayscale images.

[0102] Step S1024: converting the plurality of second region grayscale images into a plurality of second region brightness images according to the grayscale-brightness mapping relationship.

[0103] Step S1025: calculating the brightness mean value in the corresponding second region for each of the plurality of second region brightness images, to obtain a plurality of unit mean brightness images corresponding to the plurality of second region brightness images.

[0104] For example, the above embodiment can be applied to non-spliced ​​screens or spliced ​​screens comprising multiple sub-displays, and this disclosure does not limit this. The multiple sub-displays of a spliced ​​screen can be spliced ​​in n rows and m columns, where n and m are positive integers and at least one is greater than 1. This disclosure does not limit the splicing method. In this disclosure, a non-spliced ​​screen can be considered to include a single sub-display, that is, it itself serves as a sub-display.

[0105] For example, in step S1021, for a non-spliced ​​screen, the first grayscale image is divided into multiple first regions of equal size, and the multiple first regions correspond to multiple first region grayscale images. It should be noted that the embodiment of the present disclosure does not limit the size and number of the first region grayscale images and can be adjusted according to actual needs.

[0106] For example, in step S1021, for a spliced ​​screen, assuming that each sub-display screen has a size of 160×180 pixels, the first grayscale image is divided into multiple first regions of equal size. The multiple first regions correspond to multiple first-region grayscale images, and the size of the first-region grayscale images is the same as the size of the sub-display screen. That is, each sub-display screen corresponds to one of the multiple first-region grayscale images. It should be noted that the embodiments of the present disclosure do not impose any restrictions on the size and number of the first-region grayscale images, and these can be adjusted based on actual needs.

[0107] For example, in step S1022, in order to reduce the complexity of storage and calculation while ensuring the basic pattern outline, each first-region grayscale image is divided into multiple second regions of the same size. For each first-region grayscale image, the grayscale mean of the grayscale image pixels in each second region is calculated to obtain multiple second-region grayscale images. For example, the first-region grayscale image of size 160×180 pixels is downsampled and divided into 8×9 second regions of size 20×20 pixels. The grayscale mean of the grayscale image pixels in each second region is calculated to obtain a numerical value representing the overall grayscale characteristics of the region, thereby obtaining multiple second-region grayscale images of size 8×9. It should be noted that the embodiments of the present disclosure do not limit the size and number of the second-region grayscale images, and can be adjusted according to actual conditions.

[0108] For example, in step S1023, the grayscale values ​​of all pixels in each second area are first accumulated to obtain the grayscale cumulative value of the second area. For example, the total number of pixels in the second area of ​​20×20 size is 400. When performing the grayscale mean operation, a division operation is required, that is, the grayscale cumulative value of the second area is divided by 400. For example, in order to adapt to the fixed-point processing in the hardware or algorithm, the division by 400 operation needs to be converted into a fixed-point form of multiplication by (1 / 400), that is, (1 / 400) is multiplied by 2 14A fixed-point scalar 41 is obtained. The accumulated grayscale value of the second region is then multiplied by the fixed-point scalar 41, converting the division operation into a multiplication operation while maintaining the fixed-point data format. After the multiplication operation, the resulting value is the fixed-point regional grayscale value. To meet 8-bit storage and display requirements, the regional grayscale values ​​are shifted and rounded, ultimately resulting in an 8-bit representation of the second regional grayscale image. Each second region corresponds to a second regional grayscale image.

[0109] For example, in step S1024, the plurality of second region grayscale images represented by 8 bits may be converted into a plurality of second region brightness images represented by 10 bits according to the grayscale-brightness mapping relationship with reference to the content of step 102, which will not be repeated here.

[0110] For example, in step S1025, in the process of further simplifying the brightness representation, the second area brightness image of size 8×9 is further reduced to a unit mean brightness image of size 1×1, that is, the brightness mean in the corresponding second area is calculated for each second area brightness image. This process also involves division operations, which need to be fixed-point processed to adapt to hardware or algorithm requirements. For example, first calculate the brightness accumulation value in the 8×9 area. For example, there are 72 brightness values ​​in the 8×9 area. When performing the brightness mean operation, a division operation is required, that is, the brightness accumulation value in the 8×9 area is divided by 72. In order to adapt to the fixed-point processing in the hardware or algorithm, the division by 72 operation needs to be converted into a fixed-point form of multiplication by (1 / 72), that is, (1 / 72) is multiplied by 2 15 This results in a fixed-point scalar value of 455. The accumulated brightness value within the 8×9 region is then multiplied by this fixed-point scalar value, converting the division operation into a multiplication operation while maintaining the fixed-point data format. The resulting value is a fixed-point regional brightness value. These regional brightness values ​​are shifted and rounded, ultimately resulting in a 10-bit unit mean brightness image. Each second-region grayscale image corresponds to a unit mean brightness image.

[0111] For example, after step S1025, step 102 in the above example further includes steps S1026-S1028:

[0112] Step S1026: performing a boundary search on the mean brightness image to obtain a boundary search map, wherein the mean brightness image includes all unit mean brightness images.

[0113] For example, the mean intensity image is a complete image consisting of all 1×1 unit mean intensity images.

[0114] For example, in step S1026, the boundary regions of the mean luminance image are searched in multiple directions, and the searched regions are assigned values ​​according to the boundary search lookup table to obtain multiple sub-boundary search maps. For example, the multiple directions can be from top to bottom, from right to left, from bottom to top, and from left to right, but this is not limited in the embodiments of the present disclosure.

[0115] For example, in step S1026 , multiple sub-boundary search graphs are superimposed to obtain a boundary search graph.

[0116] FIG4 is a schematic diagram of a boundary search method provided by at least one embodiment of the present disclosure.

[0117] For example, a brightness threshold is first set, such as 307. Boundary areas below this threshold are considered low-brightness boundary areas, and otherwise are considered high-brightness boundary areas. It should be noted that other values ​​can also be set as brightness thresholds, and the embodiments of the present disclosure are not limited thereto.

[0118] For example, as shown in Figure 4, starting from the first boundary region (boundary region No. 1) of the mean brightness image boundary (outermost circle), the boundary regions are searched one by one along the specified direction (for example, the direction 1-25). When a high-brightness boundary region with a brightness higher than the brightness threshold is encountered, the search in the current direction is stopped. The first high-brightness boundary region currently searched is recorded, and the low-brightness boundary regions that have been searched are assigned values ​​in the opposite direction. For example, a boundary search lookup table is used to assign specific boundary values ​​to the low-brightness boundary regions that have been searched. As shown in Table 2, the length of the boundary search lookup table is 10. If the number of search regions exceeds 10, all regions exceeding the limit are assigned the maximum value of 318. After the assignment is completed, the starting position of the search is moved, and the search continues until all boundary regions have been traversed.

[0119] Table 2: Boundary search lookup table

[0120] For example, as shown in FIG4 , starting from boundary region 1 and searching downward, boundary regions 1, 24, and 23 are sequentially found to be low grayscale boundary regions. The boundary search lookup table can be used to obtain the boundary values ​​of boundary regions 23, 24, and 1 as 20, 46, and 75, respectively. It should be noted that the above boundary search lookup table can also be adjusted according to actual needs, and the embodiments of the present disclosure are not limited thereto.

[0121] For example, as shown in FIG4 , the boundary area of ​​the mean brightness image is searched in multiple directions from top to bottom, from right to left, from bottom to top, and from left to right. After the four directions are searched independently, four sub-boundary search maps are obtained. The four sub-boundary search maps are numerically accumulated to obtain a boundary search map.

[0122] Step S1027: Superimpose the boundary search image and the second luminance image to obtain an intermediate luminance image with the superimposed boundary effect, wherein the second luminance image includes all second region luminance images. For example, the second luminance image is a complete image composed of all 8×9 second region luminance images.

[0123] For example, as shown in Figure 4, the boundary search map is superimposed with the second luminance image to obtain an intermediate luminance image that is affected by the superimposed boundary. For example, if the boundary search map and the mean luminance image have the same size, in order to superimpose the boundary search map with the second luminance image, each 1×1 region thereof needs to be resized to 8×9. For example, the resizing operation involves copying and expanding the values ​​of the 1×1 region horizontally and vertically to obtain the values ​​of the 8×9 region.

[0124] For example, the specific calculation formula for the superposition operation is as follows:

[0125] Among them, D A represents the second brightness image, D B represents the boundary search graph, D C An intermediate brightness image representing the effect of the superposition boundary, Indicates D B The maximum value in .

[0126] The purpose of the above boundary search operation is to identify low-brightness areas at the boundaries of the mean brightness image, that is, to identify areas with discontinuous or large brightness differences that may exist in the mean brightness image. These areas are usually related to the edges of the image or locations with significant brightness changes.

[0127] Step S1028: normalizing the intermediate brightness image affected by the superimposed boundary to obtain a normalized brightness image as the first brightness image.

[0128] For example, after the boundary search is completed, the bit width of the intermediate brightness image affected by the superimposed boundary may exceed 10 bits, and it needs to be remapped to the range of 0 to 1023. The mapping operation is achieved through normalization. The value range of the brightness image affected by the superimposed boundary is 0 to 2047, so a lookup table [1 / 1, 1 / 2, 1 / 3, ..., 1 / 2045, 1 / 2046, 1 / 2047] is created and fixed-pointed, that is, the data in the lookup table are multiplied by 2 24 , and obtain the normalized coefficient matrix.

[0129] For example, the normalization operation "compensation value / maximum compensation value" can be converted into a multiplication operation "compensation value×(1 / maximum compensation value)". The normalization operation includes the following steps S401-S404:

[0130] Step S401: obtaining the maximum compensation value from the intermediate brightness image affected by the superimposed boundary.

[0131] Step S402: Find the “reciprocal fixed-point value” corresponding to the maximum compensation value from the lookup table.

[0132] Step S403: multiply all values ​​in the intermediate brightness image affected by the superimposed boundary by the above-mentioned “reciprocal fixed-point value” to obtain a fixed-point normalized value.

[0133] Step S404: rounding the fixed-point normalized value to 10 bits.

[0134] Through the above normalization operation, it is ensured that the output data is not only properly normalized but also matches the bit width required by the hardware or display device.

[0135] For example, the normalized luminance image obtained through the above normalization operation is used as the first luminance image.

[0136] For example, correspondingly, in step S110 , a first number of historical normalized brightness images accumulated in the buffer pool are weightedly fused using the time window weight to obtain a thermal time accumulation image.

[0137] For example, correspondingly, in step S103, the normalized brightness image corresponding to the first image frame is added to the cache pool, and in response to the number of historical normalized brightness images in the cache pool reaching a preset number threshold before the normalized brightness image corresponding to the first image frame is added, the historical normalized brightness image frame farthest from the current moment in the cache pool is removed.

[0138] For example, in the above example, after step S100, the method further includes: performing an intra-screen diffusion filter on the heat time accumulation image to obtain an intra-screen heat diffusion compensation map.

[0139] For example, to describe the heat diffusion phenomenon within a screen (e.g., a non-spliced ​​screen or a spliced ​​screen), a Gaussian filter kernel is used to perform a screen diffusion filter on the time-accumulated heat image to obtain a screen heat diffusion compensation map. For example, the size of the Gaussian filter kernel can be 9×9.

[0140] For example, the thermal time accumulation image can be divided into a plurality of first thermal time accumulation images of size 8×9. FIG5 is a schematic diagram of intra-screen diffusion filtering according to at least one embodiment of the present disclosure, comprising the following steps S501-S506.

[0141] Step S501: Expand the first thermal time accumulation image of size 8×9 to size 16×18 through bilinear interpolation to improve spatial resolution and filtering effect.

[0142] Step S502: Fill the first thermal time accumulation image with 16×18 size with 4 circles of all 0 values ​​to fill it to 24×26 size to ensure that the filtering operation will not be affected by the boundary effect.

[0143] Step S503: Use a 9×9 Gaussian filter kernel to perform on-screen diffusion filtering on the first 24×26 thermal time accumulation image to obtain the on-screen diffusion filtered matrix K1. For example, the filtering operation is a convolution operation. For example, the coefficients of the 9×9 Gaussian filter kernel are normalized floating-point numbers and need to be fixed-pointed before the filtering operation, that is, multiplied by 2. 18 , and obtain the fixed-point 9×9 Gaussian filter kernel.

[0144] Step S504: Calculate the screen thermal diffusion compensation value using the following formula: Screen thermal diffusion compensation value = 2 10 –1–K1.

[0145] Step S505: shifting the calculated on-screen thermal diffusion compensation value and rounding it to 10 bits.

[0146] Step S506: Expand the 16×18 size result to 160×180 size through bilinear interpolation, and finally obtain the screen thermal diffusion compensation map.

[0147] The above operations can address image compensation issues caused by uneven temperature distribution within the display. Specifically, based on the actual temperature differences at various locations within the display, a thermal diffusion model can be used to generate accurate compensation values, ultimately achieving dynamic temperature compensation for the display image.

[0148] The above embodiments may be applied to a non-splicing screen or a splicing screen including a plurality of sub-display screens, and the present disclosure does not impose any limitation thereto.

[0149] For example, when the display screen is a spliced ​​screen including multiple sub-display screens, after step S100 , the method further includes: performing inter-sub-display screen diffusion filtering on the heat time accumulation image to obtain an inter-sub-display screen heat diffusion compensation map.

[0150] For example, multiple temperature image data of different splicing screen display patterns are collected, and the multiple temperature image data are merged and normalized to obtain an inter-screen influence coefficient matrix; the inter-screen influence coefficient matrix is ​​used to perform inter-sub-display screen diffusion filtering on the heat time accumulation image to obtain an inter-sub-display screen heat diffusion compensation map.

[0151] For example, the thermal time accumulation image can be divided into multiple 8×9 first thermal time accumulation images. FIG6 is a schematic diagram of inter-screen diffusion filtering provided by at least one embodiment of the present disclosure, which is used to simulate the heat diffusion process between 9 sub-displays in a 3×3 area, including the following steps S601-S606:

[0152] Step S601: averaging the first 8×9 accumulative heat time image and reducing it to 1×1 size. The second accumulative heat time image is composed of all the first 1×1 accumulative heat time images.

[0153] Step S602: Fill the edge of the second heat time accumulation image with a circle of all zero values.

[0154] Step S603: Use the 3×3 inter-screen influence coefficient matrix to perform inter-screen diffusion filtering on the second thermal time accumulation image after filling with 0 values, and obtain the inter-screen diffusion filtered matrix K2. For example, the 3×3 inter-screen influence coefficient matrix can be obtained by collecting multiple temperature image data of different multiple splicing screen display patterns, and merging and normalizing the multiple temperature image data. For example, different patterns as shown in Figure 6 are lit in the splicing screen, and after the temperature stabilizes, the temperature image data in the screen is collected using a thermal imager. For example, the 3×3 inter-screen influence coefficient matrix is ​​a normalized floating-point number, and needs to be fixed-pointed before the filtering operation, that is, it needs to be multiplied by 2. 25 , and obtain the fixed-point 3×3 inter-screen influence coefficient matrix. For example, the above step of obtaining the 3×3 inter-screen influence coefficient matrix is ​​performed before the inter-screen diffusion filtering begins.

[0155] Step S604: Calculate the inter-screen thermal diffusion compensation value using the following formula: Inter-screen thermal diffusion compensation value = 2 10 –1–K2.

[0156] Step S605: shift the calculated inter-screen thermal diffusion compensation value and round it to 10 bits.

[0157] Step S606: Expand the 1×1 size result to 160×180 size through pixel replication, and finally obtain the inter-screen heat diffusion compensation map.

[0158] For example, after step S101, the above embodiment further includes step S701.

[0159] Step S701: obtaining a grayscale-maximum compensation value lookup table, obtaining the maximum compensation value of each pixel in the first grayscale image according to the grayscale-maximum compensation value lookup table, and obtaining a maximum compensation value map.

[0160] For example, the maximum compensation value corresponding to each grayscale is not consistent, and the maximum compensation value corresponding to high grayscale is usually higher. For example, the maximum compensation value corresponding to grayscale 255 may reach more than 20. In the case of low grayscale, such as grayscale 5, its corresponding maximum compensation value theoretically cannot exceed 5, otherwise it will cause downward overflow (that is, the compensated grayscale value will drop to a negative value). In order to determine the maximum compensation value range of different grayscales, it is necessary to obtain the brightness corresponding to different grayscales when the screen temperature is the lowest and the brightness corresponding to the screen temperature is the highest, and the difference between the grayscale value at the lowest temperature and the grayscale value at the highest temperature under the same brightness is used as the maximum compensation value of the grayscale value at the highest temperature. Based on the above method, a grayscale-maximum compensation value lookup table can be constructed, covering all grayscales from grayscale 0-255 and their respective corresponding maximum compensation values, as shown in Table 3:

[0161] Table 3: Grayscale-maximum compensation value lookup table

[0162] It should be noted that the grayscale-maximum compensation value lookup table can also be adjusted according to actual needs, and the present disclosure does not limit this.

[0163] For example, the first grayscale image and the output maximum compensation value image both have a bit width of 8 bits.

[0164] For example, step S200 includes steps S1041 to S1042.

[0165] Step S1041: Processing the maximum compensation value map based on the intra-screen thermal diffusion compensation map and / or the inter-screen thermal diffusion compensation map to obtain a composite compensation map.

[0166] For example, when the display screen is a spliced ​​screen including multiple sub-display screens, the maximum compensation value map can be processed based on the intra-screen thermal diffusion compensation map and the inter-screen thermal diffusion compensation map to obtain a composite compensation map, or the maximum compensation value map can be processed by either the intra-screen thermal diffusion compensation map or the inter-screen thermal diffusion compensation map to obtain a composite compensation map. The present disclosure does not impose any restrictions on this.

[0167] For example, the intra-screen heat diffusion compensation map and the inter-screen heat diffusion compensation map can be weightedly fused to obtain a first compensation result, and then the first compensation result can be multiplied by the maximum compensation value map to obtain a composite compensation map C. final The calculation formula is as follows: final =P lv ×C max ×[P T ×C T +(1-P T )×C 3m3 ]

[0168] Among them, C 3m3 Represents the inter-screen thermal diffusion compensation diagram, C TIndicates the thermal diffusion compensation diagram inside the screen, C max Represents the maximum compensation diagram, P T Represents the unit screen thermal diffusion weight coefficient, P lv Indicates the maximum brightness coefficient.

[0169] For example, when the display screen is a non-spliced ​​screen, the composite compensation map can be obtained by multiplying the in-screen heat diffusion compensation map by the maximum compensation value map.

[0170] Step S1042 : Subtract the weighted synthetic compensation image from the three channel components in the first image frame to obtain a first compensated image frame.

[0171] For example, after obtaining the composite compensation value map, the first image frame can be compensated by performing pixel-level subtraction operations on the three channel components of the first image frame and the weighted composite compensation map. For the three independent color channels of RGB, the compensation coefficients are different. The specific calculation formula after compensation of each channel is as follows: C_R =I R -C R ×C final I C_G =I G -C G ×C final I C_B =I B -C B ×C final

[0172] Among them, I R , I G , I B are the values ​​of the RGB channels in the first image frame, I C_R , I C_G , I C_B are the values ​​after compensation of RGB three channels, C R , C G , C B They are the compensation coefficients corresponding to the RGB three channels, and the RGB three channel values ​​after compensation are I C_R , I C_G and I C_B The first image frame is integrated into an image as the output result after the final compensation processing of the current first image frame, that is, the first compensated image frame.

[0173] Based on the above operations, the synthetic compensation map integrates the dual compensation strategies of time dimension and space dimension. Among them, the spatial dimension compensation covers inter-screen thermal diffusion compensation and intra-screen thermal diffusion compensation. Through this method that comprehensively considers time and space factors, it can accurately adjust and optimize the display effect from multiple angles to ensure that the final compensation result is more accurate, thereby significantly improving the long-term stability and visual consistency of the display content.

[0174] FIG7 is a flowchart of an image processing method provided by at least one embodiment of the present disclosure. For example, as shown in FIG7 , the image processing method provided by the embodiment of the present disclosure includes the following steps S1 to S15:

[0175] Step S1: Obtain temperature rise curves when the display screen displays red, blue, and green images and the temperature fluctuation value reaches a preset range, and obtain grayscale processing proportional coefficients based on the temperature rise curves in the three cases. For example, the specific operation can be referred to the above step S1011 and will not be repeated here.

[0176] Step S2: grayscale the first image frame according to the proportional coefficient to obtain a first grayscale image corresponding to the first image frame. For example, the specific operation can refer to the above step S1012 and will not be repeated here.

[0177] Step S3: Using the time window weight, weighted fusion is performed on the first number of historical normalized brightness images accumulated in the buffer pool to obtain a thermal time accumulation image. For example, the specific operation can be referred to the above step S110 and will not be repeated here.

[0178] Step S4: Performing screen diffusion filtering on the heat time accumulation image to obtain a screen heat diffusion compensation map. For example, the specific operations can be referred to above steps S501-S506, which will not be repeated here.

[0179] Step S5: Perform inter-screen diffusion filtering on the heat time accumulation image to obtain an inter-screen heat diffusion compensation map. For example, the specific operations can be referred to above steps S601-S606, which will not be repeated here.

[0180] Step S6: weighted fusion of the intra-screen thermal diffusion compensation map and the inter-screen thermal diffusion compensation map to obtain a first compensation result. For example, the specific operation can be found in the above step S1041 and will not be repeated here.

[0181] Step S7: Obtain the maximum compensation value of each pixel in the first grayscale image according to the grayscale-maximum compensation value lookup table to obtain a maximum compensation value map. For example, the specific operation can be referred to the above step S701 and will not be repeated here.

[0182] Step S8: Fusing the first compensation result with the maximum compensation value map to obtain a composite compensation map. For example, the specific operation can refer to the above step S1041 and will not be repeated here.

[0183] Step S9: Subtract the weighted synthetic compensation map from the three channel components in the first image frame to obtain a first compensated image frame. For example, the specific operation can be found in the above step S1042 and will not be repeated here.

[0184] Step S10: performing grayscale mean processing on the first grayscale image and converting the grayscale image into a second brightness image according to the grayscale-brightness mapping relationship. For example, the specific operations can be referred to the above steps S1021-S1024, which will not be described in detail here.

[0185] Step S11: Calculate the brightness mean of the second brightness image to obtain a mean brightness image. For example, the specific operation can refer to the above step S1025 and will not be repeated here.

[0186] Step S12: Perform boundary search on the mean brightness image to obtain a boundary search map. For example, the specific operation can be referred to the above step S1026, which will not be repeated here.

[0187] Step S13: superimpose the boundary search image and the second brightness image to obtain an intermediate brightness image with the superimposed boundary effect. For example, the specific operation can be referred to the above step S1027, which will not be repeated here.

[0188] Step S14: Normalize the intermediate brightness image affected by the superimposed boundary to obtain a normalized brightness image as the first brightness image. For example, the specific operation can be found in the above step S1028 and will not be repeated here.

[0189] Step S15: The normalized luminance image (the first luminance image) is added to the buffer pool. In response to the number of historical normalized luminance images in the buffer pool reaching a preset threshold before the normalized luminance image corresponding to the first image frame is added, the historical normalized luminance image frame farthest from the current moment in the buffer pool is removed. For example, the specific operation can be found in the above-described step S103 and will not be further described here.

[0190] It should also be noted that, in the various embodiments of the present disclosure, the order in which the various steps of the image processing method are executed is not limited. Although the execution process of the various steps is described above in a specific order, this does not constitute a limitation on the embodiments of the present disclosure. The various steps in the image processing method can be executed serially or in parallel, depending on actual needs. For example, the image processing method can also include more or fewer steps, and the embodiments of the present disclosure are not limited in this regard.

[0191] At least one embodiment of the present disclosure also provides an image processing device, which is used for a display screen. It can record the historical thermal time accumulation information of the display screen based on the time window weight and the historical brightness image, obtain the current thermal time accumulation image of the display screen, and compensate the first image frame displayed on the display screen according to the thermal time accumulation image, adjust the image degree of the area with high luminous efficiency to be consistent with the chromaticity of the area with low luminous efficiency, thereby eliminating the afterimage, so that the display screen displays a uniform picture when the entire display screen switches to the same grayscale display, thereby improving the display effect and user experience.

[0192] FIG8 is a schematic block diagram of an image processing device provided by at least one embodiment of the present disclosure.

[0193] For example, as shown in FIG8 , the image processing apparatus 700 includes a time accumulation module 701 and a compensation module 702 .

[0194] For example, in at least one embodiment of the present disclosure, the time accumulation module 701 is configured to record the historical time accumulation information of the display screen's thermal state based on the time window weight and the historical brightness image, thereby obtaining the display screen's current time accumulation image of thermal state. The time window weight is used to describe the weight coefficient of the impact of the historical brightness image in the current time window on the display screen's temperature. For example, the time accumulation module 701 may implement step S100. The specific implementation method thereof may be referenced to the description of step S100 and will not be further elaborated herein.

[0195] For example, in at least one embodiment of the present disclosure, compensation module 702 is configured to compensate a first image frame among a plurality of image frames to be displayed on a display screen based on the thermal-temporal cumulative image, thereby obtaining a compensated first image frame. The first compensated image frame is then used to drive the display screen to present the first image frame. For example, compensation module 702 may implement step S200. The specific implementation method thereof may be referred to the description of step S200 and will not be further elaborated herein.

[0196] For example, in at least one embodiment of the present disclosure, the time accumulation module 701 is specifically configured to perform weighted fusion on a first number of historical brightness images accumulated in the buffer pool using time window weights to obtain a thermal time accumulation image.

[0197] For example, in at least one embodiment of the present disclosure, the image processing device 700 also includes an update module 703, which is configured to update the cache pool based on the first image frame to obtain a thermal time accumulation image corresponding to at least another image frame after the first image frame.

[0198] For example, in at least one embodiment of the present disclosure, the updating module 703 includes a grayscale unit 7031 , a grayscale-luminance conversion unit 7032 , and an updating unit 7033 .

[0199] For example, in at least one embodiment of the present disclosure, the grayscale unit 7031 is configured to perform grayscale processing on the first image frame to obtain a first grayscale image corresponding to the first image frame;

[0200] For example, in at least one embodiment of the present disclosure, the grayscale-luminance conversion unit 7032 is configured to convert the first grayscale image into a first luminance image corresponding to the first image frame according to the grayscale-luminance mapping relationship;

[0201] For example, in at least one embodiment of the present disclosure, the update unit 7033 is configured to add the first brightness image corresponding to the first image frame to the cache pool, and in response to the number of historical brightness images in the cache pool reaching a preset number threshold before the first brightness image corresponding to the first image frame is added, remove the historical brightness image frame farthest from the current moment in the cache pool.

[0202] It should be noted that these time accumulation modules 701, compensation modules 702, and update modules 703 can be implemented through software, hardware, firmware, or any combination thereof. For example, they can be implemented as a time accumulation circuit, a compensation circuit, and an update circuit, respectively. The embodiments of the present disclosure do not limit their specific implementation methods.

[0203] It should be understood that the image processing device 700 provided in the embodiment of the present disclosure can be used to implement the aforementioned image processing method, and can also achieve technical effects similar to the aforementioned image processing method, which will not be elaborated here.

[0204] It should be noted that in the embodiments of the present disclosure, the image processing device 700 may include more or fewer circuits or units, and the connection relationship between the various circuits or units is not limited and can be determined according to actual needs. The specific configuration of each circuit is not limited and can be composed of analog devices according to circuit principles, or can be composed of digital chips, or constructed in other applicable ways.

[0205] FIG9 is a schematic block diagram of another image processing apparatus provided by at least one embodiment of the present disclosure.

[0206] For example, as shown in FIG9 , the image processing apparatus 800 includes at least one processor 801 and at least one memory 802. The at least one memory 802 includes one or more computer program modules. The one or more computer program modules are stored in the at least one memory 802 and configured to be executed by the at least one processor 801. The one or more computer program modules include instructions for executing the image processing method provided by at least one embodiment of the present disclosure. When executed by the at least one processor 801, one or more steps in the image processing method provided by at least one embodiment of the present disclosure can be performed. The memory 802 and the processor 801 can be interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0207] For example, the processor 801 may be a central processing unit (CPU), a digital signal processor (DSP), or other processing units with data processing capabilities and / or program execution capabilities, such as a field programmable gate array (FPGA). For example, the central processing unit (CPU) may be an X86 or ARM architecture. The processor 801 may be a general-purpose processor or a dedicated processor, and may control other components in the image processing apparatus 800 to perform desired functions.

[0208] For example, the memory 802 may include any combination of one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), a hard disk, an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, a flash memory, etc. One or more computer program modules may be stored on the computer-readable storage medium, and the processor 801 may execute one or more computer program modules to implement the various functions of the image processing device 800. The computer-readable storage medium may also store various applications and various data, as well as various data used and / or generated by the applications. The specific functions and technical effects of the image processing device 800 can be referred to the description of the image processing method above, and will not be repeated here.

[0209] FIG10 is a schematic block diagram of another image processing device provided by at least one embodiment of the present disclosure.

[0210] The terminal devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. The image processing apparatus 900 shown in FIG10 is merely an example and should not limit the functionality and scope of use of the embodiments of the present disclosure.

[0211] For example, as shown in FIG10 , in some examples, the image processing device 900 includes a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage device 908 into a random access memory (RAM) 903. Various programs and data required for the operation of the computer system are also stored in the RAM 903. The processing device 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0212] For example, the following components may be connected to the I / O interface 905: an input device 906 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 907 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; a storage device 908 including, for example, a magnetic tape, hard disk, etc.; and a communication device 909 including, for example, a network interface card, such as a LAN card, modem, etc. The communication device 909 may allow the image processing device 900 to communicate with other devices wirelessly or wired to exchange data, performing communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. Removable media 911, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in the drive 910 as needed, so that computer programs read therefrom can be installed into the storage device 908 as needed. Although FIG. 10 illustrates the image processing device 900 as including various devices, it should be understood that implementation or inclusion of all of the devices shown is not required. More or fewer devices may alternatively be implemented or included.

[0213] For example, the image processing device 900 may further include a peripheral interface (not shown in the figure), etc. The peripheral interface may be various types of interfaces, such as a USB interface, a lightning interface, etc. The communication device 909 may communicate with a network and other devices through wireless communication, such as the Internet, an intranet, and / or a wireless network such as a cellular telephone network, a wireless local area network (LAN), and / or a metropolitan area network (MAN). Wireless communications may use any of a variety of communication standards, protocols, and technologies, including, but not limited to, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Wi-Fi (e.g., based on IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, and / or IEEE 802.11n standards), Voice over Internet Protocol (VoIP), Wi-MAX, protocols for email, instant messaging, and / or Short Message Service (SMS), or any other suitable communication protocol.

[0214] For example, the image processing device 900 can be any device such as a mobile phone, tablet computer, laptop computer, e-book, game console, television, digital photo frame, navigator, etc., or it can be any combination of data processing devices and hardware. The embodiments of the present disclosure are not limited to this.

[0215] For example, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 909, or installed from the storage device 908, or installed from the ROM 902. When the computer program is executed by the processing device 901, the image processing method disclosed in the embodiment of the present disclosure is executed.

[0216] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0217] The computer-readable medium may be included in the image processing apparatus 900 , or may exist independently without being incorporated into the image processing apparatus 900 .

[0218] FIG11 is a schematic block diagram of an electronic device according to at least one embodiment of the present disclosure.

[0219] For example, as shown in FIG11 , at least one embodiment of the present disclosure provides an electronic device 1000, comprising an image processing apparatus 1001. For example, the image processing apparatus 1001 is an image processing apparatus provided by at least one embodiment of the present disclosure, such as the image processing apparatus 700 in FIG8 or the image processing apparatus 800 in FIG9 .

[0220] For example, the electronic device provided in at least one embodiment of the present disclosure further includes a display screen 1003 and a controller 1002. The controller 1002 is configured to receive the first compensated image frame generated by the image processing device 1001 and drive the display screen 1003 to present the first image frame. The controller 1002 is coupled to the image processing device 1001 and to the display screen 1003. For example, the display screen 1003 includes a gate drive circuit, a data drive circuit, etc. The controller 1002 is coupled to the gate drive circuit, the data drive circuit, etc., and provides the gate drive circuit, the data drive circuit, etc. with gate drive signals and data drive signals generated based on the first compensated image frame. The controller, for example, includes a timing controller (Tcon).

[0221] For example, the electronic device 1000 also includes a data receiving device (not shown), which is coupled to the image processing device 1001. The data receiving device is configured to obtain image data to be displayed from a storage device (such as a memory or an external memory) or a network (such as a modem, etc.), and provide the image data to the image processing device 1001 for compensation operations.

[0222] For example, in the electronic device provided by at least one embodiment of the present disclosure, the display screen 1003 is a mini light emitting diode display screen (MLED).

[0223] For example, in the electronic device provided by at least one embodiment of the present disclosure, the display screen may be a spliced ​​screen or a non-splicing screen. The spliced ​​screen includes multiple sub-display screens, and these multiple sub-display screens spliced ​​together jointly display an image frame.

[0224] For example, an image or video signal is input into an image processing device through a dot-screen device. The image processing device processes the signal and outputs a first compensated image frame. The controller receives the first compensated image frame and drives the display screen to present it.

[0225] FIG12 is a schematic block diagram of a non-transitory readable storage medium provided by at least one embodiment of the present disclosure.

[0226] For example, as shown in FIG12 , a non-transitory readable storage medium 1100 stores computer instructions 1101 , which, when executed by a processor, perform one or more steps of the above image processing method.

[0227] For example, the non-transitory readable storage medium 1100 can be any combination of one or more computer-readable storage media. For example, one computer-readable storage medium includes computer-readable program code for recording the thermal time accumulation information of the display screen during the display process based on the time window weight and the historical brightness image to obtain the current thermal time accumulation image of the display screen. Another computer-readable storage medium includes computer-readable program code for compensating a first image frame among multiple image frames to be displayed on the display screen based on the thermal time accumulation image to obtain a compensated first compensated image frame. Of course, the above-mentioned program codes can also be stored in the same computer-readable medium, and the embodiments of the present disclosure are not limited to this.

[0228] For example, when the program code is read by a computer, the computer can execute the program code stored in the computer storage medium and perform, for example, the image processing method provided by any embodiment of the present disclosure.

[0229] For example, the storage medium may include a memory card in a smartphone, a storage component in a tablet computer, a hard disk in a personal computer, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a flash memory, or any combination thereof, or other suitable storage media. For example, the readable storage medium may also be the memory 802 in FIG. 9 , and the related description may refer to the above content and will not be repeated here.

[0230] At least one embodiment of the present disclosure provides a computer program product, including a computer program / instruction, wherein when the computer program / instruction is executed by at least one processor, the image processing method provided by at least one embodiment of the present disclosure is performed.

[0231] Although the present disclosure has been described in detail above using general descriptions and specific embodiments, it will be apparent to those skilled in the art that modifications or improvements may be made based on the embodiments of the present disclosure. Therefore, such modifications or improvements, as long as they do not depart from the spirit of the present disclosure, are within the scope of protection claimed by the present disclosure.

[0232] Regarding this disclosure, the following points need to be explained:

[0233] (1) The drawings of the embodiments of the present disclosure only relate to the structures related to the embodiments of the present disclosure. Other structures may refer to conventional designs.

[0234] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present disclosure, the thickness of layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale.

[0235] (3) In the absence of conflict, the embodiments of the present disclosure and the features therein may be combined with each other to form new embodiments.

[0236] The above description is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. The protection scope of the present disclosure shall be based on the protection scope of the claims.

Claims

1. An image processing method for a display screen, comprising: Recording historical thermal time accumulation information of the display screen based on a time window weight and a historical brightness image, and obtaining a current thermal time accumulation image of the display screen, wherein the time window weight is used to describe a weight coefficient of the current influence of the historical brightness image in the current time window on the temperature of the display screen; A first image frame among a plurality of image frames to be displayed on the display screen is compensated according to the heat time accumulation image to obtain a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

2. The image processing method according to claim 1, wherein: The step of recording historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain a current heat time accumulation image of the display screen includes: The time window weight is used to perform weighted fusion on a first number of historical brightness images accumulated in a buffer pool to obtain the heat time accumulation image.

3. The image processing method according to claim 2, further comprising, after obtaining the current thermal time accumulation image of the display screen: The buffer pool is updated based on the first image frame to obtain a thermal time accumulation image corresponding to at least another image frame after the first image frame.

4. The image processing method according to claim 3, wherein: The updating of the buffer pool based on the first image frame includes: performing grayscale processing on the first image frame to obtain a first grayscale image corresponding to the first image frame; converting the first grayscale image into a first brightness image corresponding to the first image frame according to a grayscale-brightness mapping relationship; The first brightness image corresponding to the first image frame is added to the cache pool, and in response to the number of historical brightness images in the cache pool reaching a preset number threshold before the first brightness image corresponding to the first image frame is added, the historical brightness image frame farthest from the current moment in the cache pool is removed.

5. The image processing method according to claim 4, wherein: The grayscale processing of the first image frame to obtain a first grayscale image corresponding to the first image frame includes: Obtaining temperature rise curves when the display screen displays red, blue, and green images and the temperature fluctuation value reaches a preset range, and obtaining a proportional coefficient of the grayscale processing according to the temperature rise curves in the three cases; The first image frame is grayscaled according to the proportional coefficient to obtain a first grayscale image corresponding to the first image frame. The image processing method according to claim 4 , wherein: The converting the first grayscale image into a first brightness image corresponding to the first image frame according to the grayscale-brightness mapping relationship includes: Dividing the first grayscale image into a plurality of first regions of the same size, wherein the plurality of first regions correspond to a plurality of first region grayscale images; Dividing each of the first region grayscale images into a plurality of second regions of equal size; For each grayscale image in the first region, the grayscale mean value of each grayscale image pixel in the second region is calculated to obtain a plurality of second region grayscale images. converting the plurality of second region grayscale images into a plurality of second region brightness images according to the grayscale-brightness mapping relationship, A brightness mean value in the corresponding second region is calculated for each of the plurality of second region brightness images to obtain a plurality of unit mean brightness images corresponding to the plurality of second region brightness images.

7. The image processing method according to claim 6, wherein: After obtaining the plurality of unit mean brightness images corresponding to the plurality of second region brightness images, converting the first grayscale image into a first brightness image corresponding to the first image frame according to the grayscale-brightness mapping relationship further includes: Performing a boundary search on the mean brightness image to obtain a boundary search graph, wherein the mean brightness image includes all unit mean brightness images; superimposing the boundary search image with the second brightness image to obtain an intermediate brightness image with superimposed boundary influence, wherein the second brightness image includes the entire second region brightness image; The intermediate brightness image affected by the superposition boundary is normalized to obtain a normalized brightness image as the first brightness image.

8. The image processing method according to claim 7, wherein: The performing boundary search on the mean brightness image to obtain a boundary search graph includes: Searching for boundary areas of the mean brightness image in multiple directions, assigning values to the searched areas according to a boundary search lookup table, and obtaining multiple sub-boundary search maps; The plurality of sub-boundary search graphs are superimposed to obtain the boundary search graph.

9. The image processing method according to claim 4, further comprising: after grayscale processing is performed on the first image frame to obtain a first grayscale image corresponding to the first image frame: Obtain a grayscale-maximum compensation value lookup table; The maximum compensation value of each pixel in the first grayscale image is obtained according to the grayscale-maximum compensation value lookup table to obtain a maximum compensation value map.

10. The image processing method according to claim 9, wherein: The step of obtaining a grayscale-maximum compensation value lookup table includes: Get the brightness of different grayscales at the lowest temperature and the brightness at the highest temperature; The difference between the grayscale value at the lowest temperature and the grayscale value at the highest temperature under the same brightness is used as the maximum compensation value of the grayscale value at the highest temperature, and the grayscale-maximum compensation value lookup table is constructed.

11. The image processing method according to claim 10, wherein: The compensating the first image frame according to the heat time accumulation image to obtain a compensated first compensated image frame includes: Processing the maximum compensation value map based on the intra-screen heat diffusion compensation map and / or the inter-screen heat diffusion compensation map to obtain a synthetic compensation map; The weighted synthetic compensation image is subtracted from the three channel components in the first image frame to obtain the first compensated image frame.

12. The image processing method according to any one of claims 1 to 11, wherein: Before recording the historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current heat time accumulation image of the display screen, the method further includes: Obtaining a temperature rise curve from when the display screen is turned on to when the temperature fluctuation value reaches a preset range when the display screen displays a full white screen; The time window weight is obtained based on the temperature rise curve.

13. The image processing method according to any one of claims 1 to 12, wherein: The compensating a first image frame among a plurality of image frames to be displayed on the display screen according to the heat time cumulative image to obtain a compensated first compensated image frame includes: The weighted heat time accumulation image is subtracted from the three channel components in the first image frame to obtain the first compensated image frame.

14. The image processing method according to any one of claims 1 to 13, wherein: The display screen is a spliced screen including multiple sub-display screens. The image processing method, after recording the historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current heat time accumulation image of the display screen, further includes: The heat time accumulation image is subjected to inter-sub-display screen diffusion filtering to obtain an inter-sub-display screen heat diffusion compensation map.

15. The image processing method according to claim 14, wherein: The step of performing inter-sub-display screen diffusion filtering on the heat time accumulation image to obtain an inter-sub-display screen heat diffusion compensation map includes: Collecting a plurality of temperature image data of different splicing screen display patterns, and obtaining an inter-screen influence coefficient matrix after merging and normalizing the plurality of temperature image data; The inter-screen influence coefficient matrix is used to perform inter-sub-screen diffusion filtering on the heat time accumulation image to obtain the inter-sub-screen heat diffusion compensation map.

16. The image processing method according to any one of claims 1 to 15, wherein: The display screen includes at least one sub-display screen, The image processing method, after recording the historical heat time accumulation information of the display screen based on the time window weight and the historical brightness image to obtain the current heat time accumulation image of the display screen, further includes: The heat time accumulation image is subjected to the diffusion filtering within the at least one sub-display screen to obtain a heat diffusion compensation map within the at least one sub-display screen.

17. The image processing method according to claim 16, wherein: Performing diffusion filtering within the at least one sub-display screen on the comprehensive historical influence map to obtain a heat diffusion compensation map within the at least one sub-display screen includes: A Gaussian filter kernel is used to perform diffusion filtering within the at least one sub-display screen on the heat time accumulation image to obtain a heat diffusion compensation map within the at least one sub-display screen.

18. An image processing device for a display screen, comprising: a time accumulation module configured to record historical thermal time accumulation information of the display screen based on a time window weight and a historical brightness image, and obtain a current thermal time accumulation image of the display screen, wherein the time window weight is used to describe a weight coefficient of the current influence of the historical brightness image in the current time window on the temperature of the display screen; A compensation module is configured to compensate a first image frame among multiple image frames to be displayed on the display screen according to the heat time accumulation image to obtain a compensated first compensated image frame, wherein the first compensated image frame is used to drive the display screen to present the first image frame.

19. An image processing apparatus, comprising: at least one processor; at least one memory including one or more computer program modules; The one or more computer program modules are stored in the at least one memory and configured to be executed by the at least one processor, and the one or more computer program modules include instructions for executing the image processing method according to any one of claims 1 to 17.

20. An electronic device comprising: The image processing device according to claim 18 or 19.

21. The electronic device according to claim 20, further comprising: the display screen; The controller is configured to receive the first compensated image frame generated by the image processing device to drive the display screen to present the first image frame.

22. A non-transitory readable storage medium having computer instructions stored thereon, wherein: When the computer instructions are executed by at least one processor, the image processing method according to any one of claims 1 to 17 is performed.

23. A computer program product comprising a computer program / instructions, wherein: When the computer program / instructions are executed by at least one processor, the image processing method according to any one of claims 1 to 17 is performed.

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