Gray scale compensation method and device, display device, equipment and storage medium

Abstract

The invention provides a gray scale compensation method and device, a display device, equipment and a storage medium, and belongs to the technical field of display. The gray scale compensation method disclosed by the invention comprises the following steps: according to initial gray scale data and pixel position information of each pixel point in a to-be-displayed image, determining actual load intensity corresponding to the to-be-displayed image by utilizing a first association relationship; the first association relationship is an association relationship between the load intensity of the display panel and a gray scale variable; according to the initial gray scale data of each pixel point, target brightness information corresponding to each pixel point is determined by using a second association relationship; the second association relationship is an association relationship between the gray scale variable and the brightness; according to the initial gray scale data, the actual load intensity and the target brightness information of each pixel point, compensation gray scale data of each pixel point after compensation is determined by using a third association relationship, and the third association relationship is an association relationship among the gray scale variable, the load intensity and the brightness of the display panel.

Description

Grayscale compensation method and device, display device, equipment and storage medium Technical Field

[0001] The present disclosure belongs to the field of display technology, and particularly relates to a grayscale compensation method and device, a display device, equipment, and a storage medium. Background Art

[0002] Organic light-emitting diodes (OLEDs), as current-mode light-emitting devices, are increasingly being used in high-performance displays. Due to their self-luminous properties, active-matrix organic light-emitting diode (AMOLED) panels offer numerous advantages over liquid crystal displays (LCDs), such as high contrast, ultra-thinness, and flexibility, leading to their widespread adoption.

[0003] Figure 1 is a schematic diagram of an AMOLED pixel circuit. As shown in Figure 1, it primarily consists of two thin-film transistors (TFTs), which provide current to the OLED device. Typically, OLED brightness is proportional to the current supplied by the TFTs, which is dependent on their characteristic parameters. Due to manufacturing limitations, the current is affected by multiple factors, including TFT mobility, threshold voltage, OLED drive voltage, and power supply voltage, leading to non-uniform display brightness.

[0004] Summary of the Invention

[0005] The present disclosure aims to solve at least one of the technical problems existing in the prior art and provides a grayscale compensation method and device, a display device, an apparatus and a storage medium.

[0006] In a first aspect, the technical solution adopted to solve the technical problem of the present disclosure is a grayscale compensation method, which is applied to the display of a display panel, wherein the grayscale compensation method includes: acquiring multiple frames of images to be displayed, and performing grayscale compensation on the images to be displayed to obtain compensated grayscale data;

[0007] The performing grayscale compensation on the image to be displayed to obtain compensated grayscale data includes:

[0008] determining, based on initial grayscale data and pixel position information of each pixel in the image to be displayed, an actual load intensity corresponding to the image to be displayed using a pre-established first association relationship; the first association relationship being an association relationship between the load intensity of the display panel and the grayscale variable;

[0009] Determining target brightness information corresponding to each pixel point based on initial grayscale data of each pixel point in the image to be displayed using a pre-established second association relationship; the second association relationship is an association relationship between the grayscale variable and brightness;

[0010] According to the initial grayscale data of each pixel point in the image to be displayed, the actual load intensity and the target brightness information, the compensated grayscale data of each pixel point after compensation is determined using a pre-established third association relationship, wherein the third association relationship is the association relationship between the grayscale variable and the load intensity and the brightness of the display panel.

[0011] In some embodiments, the grayscale compensation method further includes the step of pre-establishing a first correlation between the load intensity of the display panel and the grayscale variable, including:

[0012] A first correlation relationship between the load intensity of the display panel and the grayscale variable is established based on the predetermined load intensity weight values ​​of the red R, green G, and blue B channels, and the first exponential coefficient, second exponential coefficient, and third exponential coefficient of the grayscale corresponding to the R, G, and B channels respectively affecting the load intensity.

[0013] In some embodiments, before determining the load strength weight values ​​of the R, G, and B channels, the method further includes:

[0014] According to a first preset strategy, n first test images are generated and the display panel is controlled to display them; each of the first test images includes white pixels, and the number of white pixels in the i-th first test image accounts for i / n of the total number of pixels in the i-th first test image, where 1≤i≤n, i is a positive integer, n is a positive integer greater than 1, and n is less than or equal to the resolution of the first test image;

[0015] acquiring a first screen brightness of the white pixel cluster area in the display panel when each of the first test images is displayed;

[0016] For the i-th first test image, taking a ratio of the number of white pixels therein to the total number of pixels as a first load intensity of the i-th first test image;

[0017] A first linear relationship between load intensity and screen brightness is obtained by fitting according to the first screen brightness and the first load intensity corresponding to each of the first test images.

[0018] In some embodiments, the grayscale compensation method further includes the step of determining load intensity weight values ​​of the R, G, and B channels, including:

[0019] According to a second preset strategy, second test images corresponding to the R, G, and B channels are generated, and the display panel is controlled to display them; the second test image corresponding to the R channel includes white pixels located in a first middle area and red pixels located in a first surrounding area, the second test image corresponding to the G channel includes white pixels located in a second middle area and green pixels located in a second surrounding area, and the second test image corresponding to the B channel includes white pixels located in a third middle area and blue pixels located in a third surrounding area; the pixel positions of the white pixels in each of the second test images are the same;

[0020] acquiring a second screen brightness of a central area of ​​the display panel when each of the second test images is displayed;

[0021] Determine, based on the first linear relationship and the second screen brightness, second load intensities corresponding to the three second test images, respectively, and use them as the second load intensities corresponding to the R, G, and B channels, respectively;

[0022] The load intensity weight values ​​of the R, G, and B channels are determined based on the second load intensity corresponding to the R channel and the predefined association between the R channel load intensity and the load intensity weights of each channel, the load intensity corresponding to the G channel and the predefined association between the G channel load intensity and the load intensity weights of each channel, the load intensity corresponding to the B channel and the predefined association between the B channel load intensity and the load intensity weights of each channel, and the association between the load intensity weights corresponding to the R, G, and B channels respectively.

[0023] In some embodiments, for the second test image corresponding to the R channel, the three channel values ​​of the white pixel are all 255 grayscale, the R channel value of the red pixel is 255 grayscale, the G channel value is 0 grayscale, and the B channel value is 0 grayscale;

[0024] For the second test image corresponding to the G channel, the three channel values ​​of the white pixel are all 255 grayscale, the G channel value of the green pixel is 255 grayscale, the R channel value is 0 grayscale, and the B channel value is 0 grayscale;

[0025] For the second test image corresponding to the B channel, the three channel values ​​of the white pixel are all 255 grayscale, the B channel value of the green pixel is 255 grayscale, the R channel value is 0 grayscale, and the G channel value is 0 grayscale.

[0026] In some embodiments, the step of determining the first exponential coefficient, the second exponential coefficient, and the third exponential coefficient includes:

[0027] According to a third preset strategy, a third test image of at least partial grayscale corresponding to the three channels R, G, and B is generated, and the display panel is controlled to display the image; the third test image of at least partial grayscale corresponding to the R channel includes white pixels located in a fourth middle area and red pixels located in a fourth surrounding area, and the grayscales of the red pixels in different third test images are different; the third test image of at least partial grayscale corresponding to the G channel includes white pixels located in a fifth middle area and green pixels located in a fifth surrounding area, and the grayscales of the green pixels in different third test images are different; the third test image of at least partial grayscale corresponding to the B channel includes white pixels located in a sixth middle area and blue pixels located in a sixth surrounding area, and the grayscales of the blue pixels in different third test images are different; the pixel positions of the white pixels in each of the third test images are the same;

[0028] acquiring a third screen brightness of the middle area of ​​the display panel when each of the third test images is displayed;

[0029] Determining, based on the first linear relationship and the third screen brightness, a third load intensity of each third test image corresponding to the R channel, a third load intensity of each third test image corresponding to the G channel, and a third load intensity of each third test image corresponding to the B channel;

[0030] According to the third load intensity of each third test image corresponding to the R channel and the load intensity weight values ​​of the R, G, and B channels, the first exponential coefficient of the influence of the grayscale of the R channel on the load intensity is determined; according to the third load intensity of each third test image corresponding to the G channel and the load intensity weight values ​​of the R, G, and B channels, the second exponential coefficient of the influence of the grayscale of the G channel on the load intensity is determined; according to the third load intensity of each third test image corresponding to the B channel and the load intensity weight values ​​of the R, G, and B channels, the second exponential coefficient of the influence of the grayscale of the B channel on the load intensity is determined.

[0031] In some embodiments, for each third test image corresponding to the R channel, the three-channel values ​​of the white pixel are all 255 grayscale, the R channel value of the red pixel in the plurality of the third test images includes at least some grayscales from 0 to 255, the G channel value is 0 grayscale, and the B channel value is 0 grayscale;

[0032] For each third test image corresponding to the G channel, the three-channel values ​​of the white pixel are all 255 grayscale, the G channel value of the red pixel in the plurality of third test images includes at least some grayscales from 0 to 255, the R channel value is 0 grayscale, and the B channel value is 0 grayscale;

[0033] For each third test image corresponding to the B channel, the three-channel values ​​of the white pixel are all 255 grayscale, the B channel value of the red pixel in the plurality of third test images includes at least some grayscales from 0 to 255, the R channel value is 0 grayscale, and the G channel value is 0 grayscale;

[0034] At least some of the grayscales from 0 to 255 included in the R channel values, at least some of the grayscales from 0 to 255 included in the G channel values, and at least some of the grayscales from 0 to 255 included in the B channel values ​​are the same.

[0035] In some embodiments, the method further includes pre-establishing a second association between the grayscale variable and brightness, including:

[0036] According to a fourth preset strategy, three groups of fourth test image groups corresponding to the three channels R, G, and B are generated, and the fourth test image groups corresponding to any channel include fourth test image subsets corresponding to at least some of the grayscales from 0 to 255, each group of the fourth test image subsets includes m fourth test images, and the display panel is controlled to sequentially display the m fourth test images of each group of the fourth test image subsets; wherein, the pixels of the surrounding areas of the 1st to (m-1) / 2th fourth test images are all the same, the pixels of the surrounding areas of the (m+1) / 2+1st to mth fourth test images are all the same, and the surrounding areas of any jth fourth test image are all the same, 1≤j≤m, j and m are both positive integers, and m is an odd number greater than 1 and less than the resolution of the fourth test image; pixels in the middle area of ​​the fourth test image corresponding to the R channel are red pixels; pixels in the middle area of ​​the fourth test image corresponding to the G channel are green pixels; pixels in the middle area of ​​the fourth test image corresponding to the B channel are blue pixels; for two adjacent fourth test images in any fourth test image subgroup, the number of pixels in the middle area is different; pixels in the (m+1) / 2th fourth test image corresponding to the R channel are red pixels, pixels in the (m+1) / 2th fourth test image corresponding to the G channel are green pixels, and pixels in the (m+1) / 2th fourth test image corresponding to the B channel are blue pixels;

[0037] acquiring a fourth screen brightness of a central area of ​​the display panel when each of the fourth test images is displayed;

[0038] For any grayscale k, determining a second theoretical brightness corresponding to the maximum load intensity based on the fourth screen brightness of the m fourth test images and the ratio of the number of pixels in the central area of ​​the m fourth test images to the total number of pixels in the fourth test images; k takes any value selected from at least some of the grayscales from 0 to 255;

[0039] For each of the three channels R, G, and B, fitting a second gamma curve under maximum load intensity according to each grayscale and the second theoretical brightness at each grayscale, obtaining an expression for the second gamma curve, and determining a second gamma value;

[0040] The second association relationship is determined according to the expressions indicated by the second gamma curves corresponding to the three channels R, G, and B respectively and the second gamma value.

[0041] In some embodiments, the method further includes pre-establishing a third correlation between the grayscale variable, the load intensity, and the brightness of the display panel, including:

[0042] For any grayscale k, determine a first theoretical brightness corresponding to the minimum load intensity based on the fourth screen brightness of the m fourth test images and the ratio of the number of pixels in the central area of ​​the m fourth test images to the total number of pixels in the fourth test images;

[0043] For each of the three channels R, G, and B, fitting a first gamma curve under minimum load intensity according to each grayscale and the first theoretical brightness at each grayscale, obtaining an expression for the first gamma curve, and determining a first gamma value;

[0044] According to the linear characteristics of load intensity and brightness, the first theoretical brightness and the second theoretical brightness at grayscale k are fitted to obtain the second linear relationship between load intensity and brightness corresponding to the three channels of R, G, and B at grayscale k;

[0045] Determine actual brightness expressions corresponding to the three channels R, G, and B at grayscale k based on a second linear relationship between load intensity and brightness corresponding to the three channels R, G, and B at grayscale k, an expression of the first gamma curve corresponding to the three channels R, G, and B at grayscale k, and an expression of the second gamma curve corresponding to the three channels R, G, and B at grayscale k;

[0046] According to the actual brightness expressions corresponding to the three channels R, G, and B at grayscale k and the assumed compensation grayscale data k′, a third correlation relationship corresponding to the three channels R, G, and B at grayscale k is established; k′ is less than k.

[0047] In some embodiments, determining the compensated grayscale data of each pixel after compensation using the pre-established third association relationship based on the initial grayscale data of each pixel in the image to be displayed, the actual load intensity, and the target brightness information includes:

[0048] The initial grayscale data of each pixel point, the actual load intensity and the target brightness information are substituted into the expression indicated by the third association relationship to calculate the compensated grayscale data k′ of each pixel point after compensation.

[0049] In some embodiments, for any group of fourth test image subsets, the pixels in the surrounding areas of the 1st to (m-1) / 2th fourth test images are black pixels, and the pixels in the surrounding areas of the (m+1) / 2+1st to mth fourth test images are white pixels.

[0050] In some embodiments, for a fourth test image corresponding to the R channel at grayscale k, the R channel value of the red pixel is grayscale k, the G channel value is grayscale 0, and the B channel value is grayscale 0;

[0051] For a fourth test image corresponding to the G channel at grayscale k, the G channel value of the green pixel is grayscale k, the R channel value is grayscale 0, and the B channel value is grayscale 0;

[0052] For the fourth test image corresponding to the B channel at grayscale k, the B channel value of the blue pixel is grayscale k, the R channel value is grayscale 0, and the G channel value is grayscale 0.

[0053] In some embodiments, for 1 to (m+1) / 2 fourth test images in any fourth test image subset, the difference between the ratio of the number of pixels in the central area of ​​the (m'+1)th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central area of ​​the (m')th fourth test image to the total number of pixels in the fourth test image is equal to a first preset value, where the first preset value is any value selected from 0.1, 0.2, 0.3, or 0.4; and m' is a positive integer selected from 1 to (m+1) / 2-1.

[0054] For the (m+1) / 2 to m fourth test images in any of the fourth test image subsets, the difference between the ratio of the number of pixels in the central area of ​​the m″th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central area of ​​the m″-1th fourth test image to the total number of pixels in the fourth test image is equal to a second preset value, where the second preset value is any value selected from 0.1, 0.2, 0.3 or 0.4; the first preset value is equal to the second preset value; and m″ is a positive integer selected from (m+1) / 2+1 to m.

[0055] In a second aspect, an embodiment of the present disclosure further provides a grayscale compensation device, comprising a storage module and a grayscale compensation module;

[0056] The storage module is configured to store a pre-established first association relationship, a second association relationship, and a third association relationship; the first association relationship is an association relationship between a load intensity of a display panel and a grayscale variable; the second association relationship is an association relationship between the grayscale variable and brightness; and the third association relationship is an association relationship between the grayscale variable, the load intensity, and the brightness of the display panel;

[0057] The grayscale compensation module is configured to obtain multiple frames of images to be displayed, and for each frame of the image to be displayed, determine the actual load intensity corresponding to the image to be displayed based on the initial grayscale data and pixel position information of each pixel point in the image to be displayed, using the pre-established first association relationship; determine the target brightness information corresponding to each pixel point based on the initial grayscale data of each pixel point in the image to be displayed, using the pre-established second association relationship; and determine the compensated grayscale data of each pixel point after compensation based on the initial grayscale data, the actual load intensity and the target brightness information of each pixel point in the image to be displayed, using the pre-established third association relationship.

[0058] In a third aspect, an embodiment of the present disclosure further provides a display device, including a grayscale compensation device and a display panel;

[0059] The grayscale compensation module is configured to store a pre-established first association relationship, a second association relationship, and a third association relationship; the first association relationship is the association relationship between the load intensity of the display panel and the grayscale variable; the second association relationship is the association relationship between the grayscale variable and the brightness; the third association relationship is the association relationship between the grayscale variable, the load intensity, and the brightness of the display panel; and obtain multiple frames of images to be displayed, and for each frame of the images to be displayed, determine the actual load intensity corresponding to the image to be displayed based on the initial grayscale data and pixel position information of each pixel in the image to be displayed using the pre-established first association relationship; determine the target brightness information corresponding to each pixel based on the initial grayscale data of each pixel in the image to be displayed using the pre-established second association relationship; and determine the compensated grayscale data of each pixel after compensation based on the initial grayscale data, the actual load intensity, and the target brightness information of each pixel in the image to be displayed using the pre-established third association relationship;

[0060] The display panel is configured to display each frame of the image to be displayed according to the compensated grayscale data corresponding thereto.

[0061] In a fourth aspect, an embodiment of the present disclosure further provides a computer device, which includes: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the grayscale compensation method as described in any one of the first aspects are performed.

[0062] In a fifth aspect, an embodiment of the present disclosure further provides a computer non-volatile readable storage medium, wherein a computer program is stored on the computer non-volatile readable storage medium, and when the computer program is executed by a processor, the steps of the grayscale compensation method as described in any one of the first aspects are executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] FIG1 is a schematic diagram of a related AMOLED pixel circuit;

[0064] FIG2 is a flow chart of a grayscale compensation method provided by an embodiment of the present disclosure;

[0065] FIG3 is a schematic diagram of n first test images provided by an embodiment of the present disclosure;

[0066] FIG4 is a schematic diagram of an opr-brightness ratio fitting curve;

[0067] FIG5 is a schematic diagram of a second test image corresponding to the three channels R, G, and B provided by an embodiment of the present disclosure;

[0068] FIG6 is a schematic diagram of a third test image of grayscales 1 to 255 corresponding to the three channels R, G, and B provided by an embodiment of the present disclosure;

[0069] FIG7 is a schematic diagram of a first correlation curve between an intermediate variable and a grayscale variable provided by an embodiment of the present disclosure;

[0070] FIG8 is a schematic diagram of a second correlation curve between an intermediate variable and a grayscale variable provided by an embodiment of the present disclosure;

[0071] FIG9 is a schematic diagram of a third correlation curve between an intermediate variable and a grayscale variable provided by an embodiment of the present disclosure;

[0072] FIG10a is a schematic diagram of a fourth test image subset corresponding to grayscales 64, 128, and 255, respectively, corresponding to the R channel provided by an embodiment of the present disclosure;

[0073] FIG10 b is a schematic diagram of a fourth test image subset corresponding to 64 grayscales, 128 grayscales, and 255 grayscales corresponding to the G channel provided by an embodiment of the present disclosure;

[0074] FIG10c is a schematic diagram of a fourth test image subset corresponding to grayscales 64, 128, and 255, respectively, corresponding to the B channel according to an embodiment of the present disclosure;

[0075] FIG11 is a schematic diagram of data of a fourth screen brightness under some grayscales extracted according to an embodiment of the present disclosure;

[0076] FIG12 is a line graph of 19 fourth test images and fourth screen brightness provided by an embodiment of the present disclosure;

[0077] FIG13 is a data diagram of a first theoretical brightness and a second theoretical brightness under a portion of grayscale corresponding to the RGB three channels provided by an embodiment of the present disclosure;

[0078] FIG14 is a schematic diagram of a second linear relationship between load intensity and brightness estimated based on the first theoretical brightness and the second theoretical brightness at grayscale k according to an embodiment of the present disclosure;

[0079] FIG15 is a schematic diagram of a specific process of grayscale compensation provided by an embodiment of the present disclosure;

[0080] FIG16 is a schematic diagram of a display device provided by an embodiment of the present disclosure;

[0081] FIG17 is a schematic structural diagram of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the disclosure for which protection is sought, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present disclosure.

[0083] Unless otherwise defined, the technical or scientific terms used in this disclosure should have the usual meanings understood by people with ordinary skills in the field to which this disclosure belongs. The words "first", "second" and similar words used in this disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one", "an" or "the" do not indicate a quantity limitation, but rather indicate the existence of at least one. 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.

[0084] In this disclosure, "multiple or several" refers to two or more. "And / or" describes the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0085] In the related art, as shown in Figure 1, the luminance of an OLED is generally proportional to the current, which is related to the characteristic parameters of the TFT. For example, due to processing limitations, the current is affected by multiple factors such as TFT mobility, threshold voltage, OLED drive voltage, and power supply voltage, resulting in non-uniformity in display brightness. For example, due to the influence of the display panel voltage drop (IR Drop), the brightness of the same grayscale in different displayed images varies greatly. To solve the problem of non-uniform display brightness, grayscale compensation is required for the pixels. The main purpose of grayscale compensation is to eliminate the influence of the above-mentioned factors and ultimately ensure that the brightness of all pixels reaches the ideal value.

[0086] Grayscale compensation methods are generally categorized as internal and external. Internal compensation utilizes a subcircuit built within the pixel using TFTs. External compensation utilizes an external driver circuit or device to sense the pixel's electrical or optical characteristics and then perform compensation. Internal compensation typically involves a complex pixel structure and drive method, and the compensation effect is limited to TFT threshold voltage and IR drop compensation, resulting in a narrow compensation range. External compensation, on the other hand, offers advantages such as a simple pixel structure, fast drive speed, and a wide compensation range.

[0087] The embodiments of the present disclosure provide a grayscale compensation method for the problem of uneven pixel brightness caused by IR Drop, which performs targeted compensation on different display images to be compensated, so that the brightness of the same grayscale on the screen remains basically consistent.

[0088] This grayscale compensation method is mainly used for display of display panels; the execution subject of this grayscale compensation method can be a display panel used for displaying images, or a computer device capable of performing certain computer operations, or a chip with certain computing capabilities, etc.

[0089] The grayscale compensation method can acquire multiple frames of images to be displayed through an acquisition device, and perform grayscale compensation on any frame of the images to be displayed, thereby obtaining compensated grayscale data.

[0090] Here, the image to be displayed may be a picture in the target environment captured in real time by a capture device, or may be a picture of a video to be played that is prepared in advance.

[0091] The grayscale compensation method for any frame of the image to be displayed is as follows: FIG2 is a flow chart of a grayscale compensation method provided by an embodiment of the present disclosure, as shown in FIG1 , including steps S11 to S13 .

[0092] S11 , determining an actual load intensity corresponding to the image to be displayed based on initial grayscale data and pixel position information of each pixel in the image to be displayed and using a pre-established first association relationship.

[0093] The initial grayscale data of a pixel point can be understood as the grayscale of the three channels (red R, green G, blue B) of the pixel at the position where the pixel point is located, that is, the channel values ​​of the three channels.

[0094] Pixel position information is the coordinate information of the location of the pixel point, for example (x, y), where x can represent both the horizontal coordinate and the number of rows of pixels in the image to be displayed; y can represent both the vertical coordinate and the number of columns of pixels in the image to be displayed.

[0095] The first correlation is the correlation between the load intensity of the display panel and the grayscale variable. The load intensity (I) of the display panel is related to the number of illuminated pixels on the display panel. The more illuminated pixels there are, the greater the load intensity (I). The load intensity is a variable that takes values ​​in the interval [0,1]. When the grayscale of all pixels in the display panel is 255, that is, the entire screen is white, I = 1; when the grayscale of all pixels in the display panel is 0, that is, the entire screen is black, I = 0. The grayscale variable refers to the grayscale of the transformable pixel, including the channel values ​​of the three channels R, G, and B. The first correlation is the correlation between the load intensity of the display panel and the grayscale variable. As the grayscale changes, the load intensity changes accordingly.

[0096] The first correlation relationship is shown in the following formula 1:

[0097] Where I represents the load intensity; H×W represents the resolution of the image to be displayed; i and j represent the rows and columns of pixels; w R 、w G 、w B Respectively represent the load intensity weight values ​​of the R, G, and B channels; g R 、g G 、g B Respectively represent the first exponential coefficient, second exponential coefficient, and third exponential coefficient of the grayscale of the three channels R, G, and B that affect the load intensity; Indicates the channel value (i.e. grayscale) of the R channel of the (i, j)th pixel in the image to be displayed, Indicates the channel value (i.e. grayscale) of the G channel of the (i, j)th pixel in the image to be displayed. Indicates the channel value (i.e. grayscale) of the B channel of the (i, j)th pixel in the image to be displayed.

[0098] Specifically, according to the channel value of the R channel, the channel value of the G channel and the channel value of the B channel of each pixel point in the image to be displayed, as well as the pixel position information (i, j) of each pixel point, the actual load intensity I corresponding to the image to be displayed is determined using the pre-established first association relationship.

[0099] S12 , determining target brightness information corresponding to each pixel point according to the initial grayscale data of each pixel point in the image to be displayed using a pre-established second association relationship.

[0100] The second correlation relationship is the correlation relationship between the grayscale variable and the brightness. As the grayscale changes, the brightness changes accordingly.

[0101] The second correlation relationship is shown in the following formula 2:

[0102] Among them, L R (k) represents the brightness of grayscale k under the R channel; L R (255) represents the brightness of 255 grayscale under the R channel; Indicates the second Gamma value under the R channel. G (k) represents the brightness of grayscale k under the G channel; L G (255) represents the brightness of 255 grayscale in the G channel; Indicates the second Gamma value under the G channel. L B (k) represents the brightness of grayscale k under the B channel; L B(255) indicates the brightness of 255 grayscale in the B channel; Indicates the second Gamma value under the B channel.

[0103] Specifically, according to the channel value of the R channel, the channel value of the G channel, and the channel value of the B channel of each pixel in the image to be displayed, the target brightness information under the three channels of R, G, and B corresponding to each pixel is determined according to Formula 2. and

[0104] Among them, k R 、k G and k B They represent the channel value of the R channel, the channel value of the G channel, and the channel value of the B channel respectively.

[0105] S13 , determining compensated grayscale data of each pixel after compensation using a pre-established third association relationship according to the initial grayscale data, actual load intensity, and target brightness information of each pixel in the image to be displayed.

[0106] The third correlation is a correlation between the grayscale variable, the load intensity, and the brightness of the display panel. As the grayscale variable and / or the load intensity changes, the brightness of the display panel changes accordingly.

[0107] The third correlation relationship is shown in the following formula 3:

[0108] Among them, L R (k, I) represents the brightness of the display panel when the R channel is at grayscale k and load intensity I; Indicates the brightness of 255 grayscale under R channel when I=0; k R Indicates the channel value of the R channel (i.e. grayscale); Indicates the first Gamma value of the R channel when I=0; k′ R Represents the compensated grayscale data of the R channel; Indicates the brightness of 255 grayscale under R channel when I=1; Indicates the second Gamma value of the R channel when I=1. G (k, I) represents the brightness of the display panel when the grayscale is k and the load intensity is I under the G channel; Indicates the brightness of 255 grayscale in the G channel when I=0; k G Indicates the channel value of the G channel (i.e. grayscale); Indicates the first Gamma value of the G channel when I=0; k′ GIndicates the compensated grayscale data of the G channel; Indicates the brightness of 255 grayscale in the G channel when I=1; Indicates the second Gamma value of the G channel when I=1. B (k, I) represents the brightness of the display panel when the grayscale is k and the load intensity is I under the B channel; Indicates the brightness of 255 grayscale in channel B when I=0; k B Indicates the channel value of the B channel (i.e. grayscale); Indicates the first Gamma value of the B channel when I=0; k′ B Indicates the compensated grayscale data of the B channel; Indicates the brightness of 255 grayscale in channel B when I=1; Indicates the second gamma value of the B channel when I=1.

[0109] Specifically, the channel value of the R channel, the channel value of the G channel, the channel value of the B channel and the actual load intensity of each pixel in the image to be displayed are substituted into Formula 3, and L is set to R (k, I) is equal to the brightness data indicated by the target brightness information under the R channel, and Let L G (k,I) is equal to the brightness data indicated by the target brightness information under the G channel Let L B (k,I) is equal to the brightness data indicated by the target brightness information under the B channel Finally, the pixel k' after compensation of R, G, and B channels is calculated. R , k′ G and k′ B .

[0110] The disclosed embodiments pre-establish a relationship model between grayscale, load intensity, and brightness, namely, a first correlation, a second correlation, and a third correlation. Based on the relationship model, a compensation algorithm for a specific grayscale under a specific load intensity is designed, ultimately achieving consistent brightness of the same grayscale under different voltage drop levels. The disclosed embodiments employ an external compensation method, which uses an external device to sense the optical characteristics of pixels and construct a relationship model between grayscale, load intensity, and brightness. This method achieves grayscale compensation with a simple compensation method, fast drive speed, and a wider compensation range.

[0111] In some embodiments, the grayscale compensation method also includes a step of pre-establishing a first correlation between the load intensity of the display panel and the grayscale variable, specifically including establishing a first correlation between the load intensity of the display panel and the grayscale variable based on predetermined load intensity weight values ​​of the red R, green G, and blue B channels, and a first exponential coefficient, a second exponential coefficient, and a third exponential coefficient of the grayscale corresponding to the R, G, and B channels, respectively, that affect the load intensity.

[0112] The specific process of determining the load intensity weight value and the exponential coefficient is introduced below.

[0113] First, before determining the load intensity weight value, it is also necessary to determine the first linear relationship between the load intensity and the screen brightness, see steps S21 to S24.

[0114] S21 . Generate n first test images according to a first preset strategy, and control the display panel to display them.

[0115] Each first test image includes white pixels, and the number of white pixels in the i-th first test image accounts for i / n of the total number of pixels in the i-th first test image, where 1≤i≤n, i is a positive integer, n is a positive integer greater than 1, and n is less than or equal to the resolution of the first test image. The resolution of the first test image is the same as the physical resolution of the display panel.

[0116] From the first test image to the nth first test image, the center position of the white pixel first test image continuously expands toward the edge position.

[0117] The distribution of white pixels in the first test image is related to the position where the brightness of the first screen is subsequently collected. For example, the position of the clustering area of ​​white pixels is also the position where the brightness of the first screen of the display panel is subsequently measured. For example, if the clustering area of ​​white pixels is the middle area of ​​the first test image, the middle area of ​​the display panel when displaying the first test image is measured using a color analyzer. If the clustering area of ​​white pixels is the upper left corner of the first test image, the upper left corner area of ​​the display panel when displaying the first test image is measured using a color analyzer. However, due to the influence of temperature diffusion, the brightness measured is more accurate when it is expanded outward from the middle area.

[0118] Figure 3 is a schematic diagram of n first test images provided by an embodiment of the present disclosure. As shown in Figure 3, the first preset strategy is as follows: the white pixel clustering area is a circular area located in the middle of the first test image, the number of white pixels in the first first test image accounts for 1 / n of the total number of pixels in the first first test image, and the remaining 9 / n are black pixels; the number of white pixels in the second first test image accounts for 2 / n of the total number of pixels in the second first test image, and the remaining 8 / n are black pixels; ...; the number of white pixels in the i-th first test image accounts for i / n of the total number of pixels in the i-th first test image, and the remaining (ni) / n are black pixels; ..., the number of white pixels in the n-1th first test image accounts for (n-1) / n of the total number of pixels in the n-1th first test image, and the remaining 1 / n are black pixels; the number of white pixels in the n-th first test image accounts for n / n=1 of the total number of pixels in the n-1th first test image.

[0119] For example, the channel values ​​of the R, G, and B channels of the white pixels in the white pixel cluster area are all 255, that is, the grayscale is 255. The channel values ​​of the R, G, and B channels of the black pixels in the non-cluster area are all 0, that is, the grayscale is 0, which is an unlit state.

[0120] S22. Obtain a first screen brightness of a white pixel cluster area in the display panel when each first test image is displayed.

[0121] The first screen brightness is the brightness at the center of the display panel when the first test image is displayed, as measured by the CA410 color analyzer. Figure 4 is a schematic diagram of the opr-brightness ratio fitting curve. As shown in Figure 4, the horizontal axis opr represents the ratio of the number of white pixels in a first test image to the total number of pixels in the first test image; the vertical axis y represents the ratio of the first screen brightness corresponding to the first test image to the brightness when opr = 1.

[0122] According to the broken line shown in Figure 4, a dotted line can be fitted to obtain the relationship between the brightness y of the white pixel and the opr value x at grayscale 255, as shown in the following formula 4:

[0123] Where u represents the first screen brightness of the white pixel cluster area; v represents the opr value; It indicates the screen brightness when the full screen is lit at 255 grayscale, that is, the first screen brightness when opr=1; a is a parameter.

[0124] S23 . For the i-th first test image, use the ratio of the number of white pixels to the total number of pixels therein as the first load intensity of the i-th first test image.

[0125] Since the load intensity (I) is related to the number of illuminated pixels on the display panel, the greater the number of illuminated pixels, the greater the load intensity (I), the smaller the drive voltage allocated to each OLED, and the dimmer the overall brightness of the display panel. Therefore, the load intensity and the overall brightness of the display panel are inversely proportional. Combined with the OPR-brightness ratio fitting curve shown in FIG4 , the load intensity and the overall brightness of the display panel are in a linear inverse relationship. Therefore, when the pixel is white, the OPR value can be assumed to be the first load intensity when the current first test image is displayed on the display panel, for use in subsequent calculations (see step S24).

[0126] S24. According to the first screen brightness and the first load intensity corresponding to each first test image, a first linear relationship between the load intensity and the screen brightness is obtained by fitting.

[0127] Assuming that the value of opr is the first load intensity when the current first test image is displayed on the display panel, the brightness of the white pixel at 255 grayscale and the load intensity I can be approximately linearly related. Therefore, the above formula 4 can also be written as the following formula 5.

[0128] The first linear relationship is shown in the following formula 5:

[0129] Wherein, u represents the first screen brightness of the white pixel cluster area; I1 represents the first load intensity; It is the screen brightness when the full screen is lit at 255 grayscale, that is, the first screen brightness when opr=1; a is a parameter, and the parameter data is known.

[0130] Afterwards, based on the determination of the first linear relationship, the load intensity weight values ​​of the three channels R, G, and B are further determined, as shown in steps S26 to S29 .

[0131] S26 . Generate second test images corresponding to the three channels R, G, and B respectively according to the second preset strategy, and control the display panel to display them.

[0132] The second test image corresponding to the R channel includes white pixels located in the first middle area and red pixels located in the first surrounding area. The second test image corresponding to the G channel includes white pixels located in the second middle area and green pixels located in the second surrounding area. The second test image corresponding to the B channel includes white pixels located in the third middle area and blue pixels located in the third surrounding area. The pixel positions of the white pixels in each second test image are the same.

[0133] For example, the first, second, and third intermediate regions have the same shape, size, and location, and the same number of white pixels in these intermediate regions. For example, the number of white pixels in the intermediate regions accounts for 30% of the total number of pixels in the second test image. Of course, other percentages may be selected, and this disclosure is not particularly limited thereto.

[0134] Figure 5 is a schematic diagram of a second test image corresponding to the R, G, and B channels, respectively, provided in an embodiment of the present disclosure. As shown in Figure 5 , the second preset strategy is as follows: the first, second, and third intermediate regions are circular regions located in the center of the second test image. The number of white pixels accounts for 30% of the total number of pixels in the second test image. The resolution of the second test image is the same as the physical resolution of the display panel.

[0135] For example, as shown in FIG5 , for the second test image corresponding to the R channel, the three channel values ​​of the white pixels are all 255 grayscale, the R channel value of the red pixels is 255 grayscale, the G channel value is 0 grayscale, and the B channel value is 0 grayscale; for the second test image corresponding to the G channel, the three channel values ​​of the white pixels are all 255 grayscale, the G channel value of the green pixels is 255 grayscale, the R channel value is 0 grayscale, and the B channel value is 0 grayscale; for the second test image corresponding to the B channel, the three channel values ​​of the white pixels are all 255 grayscale, the B channel value of the green pixels is 255 grayscale, the R channel value is 0 grayscale, and the G channel value is 0 grayscale.

[0136] Of course, for red pixels, you can also choose R channel values ​​other than 255, such as 254 or 253, and the selection range can be between 128 and 255. Similarly, for green pixels, the selection range of G channel values ​​can be between 128 and 255. For blue pixels, the selection range of B channel values ​​can be between 128 and 255.

[0137] S27. Obtain a second screen brightness of the middle area of ​​the display panel when each second test image is displayed.

[0138] The second screen brightness is the brightness of the center of the display panel when the second test image is displayed, measured by the CA410 color analyzer. It is known that the second screen brightness of the second test image corresponding to the measured R channel is u R The second screen brightness of the second test image corresponding to the measured G channel is u G The second screen brightness of the second test image corresponding to the measured B channel is u B , used for the subsequent calculation of the second load intensity, see step S28 below.

[0139] S28. Determine second load intensities corresponding to the three second test images respectively according to the first linear relationship and the second screen brightness, and use them as the second load intensities corresponding to the three channels R, G, and B respectively.

[0140] Specifically, u R 、u G and u B , respectively into formula 5, and obtain the second load intensity corresponding to the R channel The second load intensity corresponding to the G channel The second load intensity corresponding to channel B

[0141] S29. Determine the load intensity weight values ​​of the three channels R, G, and B based on the second load intensity corresponding to the R channel and the predefined association relationship between the R channel load intensity and the load intensity weights of each channel, the load intensity corresponding to the G channel and the predefined association relationship between the G channel load intensity and the load intensity weights of each channel, the load intensity corresponding to the B channel and the predefined association relationship between the B channel load intensity and the load intensity weights of each channel, and the association relationship between the load intensity weights corresponding to the three channels R, G, and B, respectively.

[0142] The predefined correlation between the R channel load intensity and the load intensity weight of each channel is shown in the following formula 6:

[0143] The predefined correlation between the G channel load intensity and the load intensity weight of each channel is shown in the following formula 7:

[0144] The predefined correlation between the B channel load intensity and the load intensity weight of each channel is shown in the following formula 8:

[0145] The correlation between the load intensity weights corresponding to the three channels R, G, and B is shown in the following formula 9: R +w G +w B =1……………….…………Formula 9

[0146] Among them, w R Indicates the load intensity weight of the R channel affecting the load intensity I; w G represents the load intensity weight of G channel affecting load intensity I; w B Indicates the load intensity weight of channel B affecting load intensity I; Indicates the second load intensity of the R channel; represents the second load intensity of G channel; represents the second load intensity of channel B; b is a fixed parameter, which is known and is related to the ratio of the number of white pixels in the middle area to the total number of pixels in the second test image. For example, if the number of white pixels in the middle area listed above accounts for 30% of the total number of pixels in the second test image, then b = 0.3.

[0147] It is known that the second load intensity corresponding to the R channel is obtained through step S28. The second load intensity corresponding to the G channel The second load intensity corresponding to channel B The load intensity weight values ​​of the three channels R, G, and B can be calculated by the equation group composed of the above formulas 6 to 8, that is, w R The value of w G The value of w B The numerical value of .

[0148] Solve the above equations to get w R 、w G 、w B However, it should be noted that due to the influence of measurement error, the w obtained by solving the first three equations is R 、w G 、w B The value of may not satisfy Formula 9. In this case, it can be normalized, that is, Just perform normalization.

[0149] Afterwards, based on the determination of the first linear relationship and the load intensity weight values ​​of the three channels R, G, and B, continue to determine the first exponential coefficient of the influence of the grayscale of the R channel on the load intensity, the second exponential coefficient of the influence of the grayscale of the G channel on the load intensity, and the second exponential coefficient of the influence of the grayscale of the B channel on the load intensity. For details, see steps S210 to S213.

[0150] S210 , generating a third test image of at least a portion of grayscale corresponding to the three channels R, G, and B respectively according to a third preset strategy, and controlling the display panel to display the image.

[0151] Among them, the third test image of at least partial grayscale corresponding to the R channel includes white pixels located in the fourth middle area and red pixels located in the fourth surrounding area, and the grayscale of the red pixels in different third test images is different. The third test image of at least partial grayscale corresponding to the G channel includes white pixels located in the fifth middle area and green pixels located in the fifth surrounding area, and the grayscale of the green pixels in different third test images is different. The third test image of at least partial grayscale corresponding to the B channel includes white pixels located in the sixth middle area and blue pixels located in the sixth surrounding area, and the grayscale of the blue pixels in different third test images is different; the pixel position of the white pixels in each third test image is the same.

[0152] For example, the fourth, fifth, and sixth intermediate regions have the same shape, size, and location, and the same number of white pixels in these intermediate regions. For example, the number of white pixels in these intermediate regions accounts for 30% of the total number of pixels in the third test image. Of course, other percentages may be selected, and this disclosure is not particularly limited thereto.

[0153] Figure 6 is a schematic diagram of a third test image with grayscales of 1 to 255 corresponding to the three R, G, and B channels, provided in an embodiment of the present disclosure. As shown in Figure 6 , the third preset strategy is as follows: the fourth, fifth, and sixth intermediate regions are circular regions located in the center of the third test image. The number of white pixels in the fourth, fifth, and sixth intermediate regions accounts for 30% of the total number of pixels in the third test image. The resolution of the second test image is the same as the physical resolution of the display panel.

[0154] For each channel, the third test image corresponding to at least a portion of the grayscale can be, for example, a third test image corresponding to a portion of the grayscale range from 0 to 255, or a third test image corresponding to all grayscales. For each channel, the more third test images corresponding to grayscales are selected, the more accurate the first association relationship established. However, this also requires a greater computational effort. Therefore, an appropriate number of third test images with grayscales can be selected to establish the first association relationship based on actual experience and product requirements.

[0155] It should be noted that the selected partial grayscales of the third test image corresponding to at least a portion of grayscales of each channel are the same.

[0156] For each third test image corresponding to the R channel, the three-channel values ​​of the white pixels are all grayscale 255, the R channel values ​​of the red pixels in the multiple third test images include at least some grayscales between 0 and 255, the G channel values ​​are grayscale 0, and the B channel values ​​are grayscale 0. For each third test image corresponding to the G channel, the three-channel values ​​of the white pixels are all grayscale 255, the G channel values ​​of the red pixels in the multiple third test images include at least some grayscales between 0 and 255, the R channel values ​​are grayscale 0, and the B channel values ​​are grayscale 0. For each third test image corresponding to the B channel, the three-channel values ​​of the white pixels are all grayscale 255, the B channel values ​​of the red pixels in the multiple third test images include at least some grayscales between 0 and 255, the R channel values ​​are grayscale 0, and the G channel values ​​are grayscale 0. At least some grayscales between 0 and 255 included in the R channel values, at least some grayscales between 0 and 255 included in the G channel values, and at least some grayscales between 0 and 255 included in the B channel values ​​are the same.

[0157] For example, the selected grayscales may be 16 grayscales, 32 grayscales, 64 grayscales, 96 grayscales, 112 grayscales, 128 grayscales, 144 grayscales, 160 grayscales, 176 grayscales, 192 grayscales, 208 grayscales, 224 grayscales, 240 grayscales, and 255 grayscales. According to the third preset strategy, a third test image of 16 grayscales, 32 grayscales, 64 grayscales, 96 grayscales, 112 grayscales, 128 grayscales, 144 grayscales, 160 grayscales, 176 grayscales, 192 grayscales, 208 grayscales, 224 grayscales, 240 grayscales, and 255 grayscales corresponding to the R channel is generated, and a third test image of 16 grayscales, 32 grayscales, 64 grayscales, 96 grayscales, 112 grayscales, 128 grayscales, 144 grayscales, The third test image of grayscale, 160 grayscale, 176 grayscale, 192 grayscale, 208 grayscale, 224 grayscale, 240 grayscale, and 255 grayscale is generated to generate a third test image of grayscale, 16 grayscale, 32 grayscale, 64 grayscale, 96 grayscale, 112 grayscale, 128 grayscale, 144 grayscale, 160 grayscale, 176 grayscale, 192 grayscale, 208 grayscale, 224 grayscale, 240 grayscale, and 255 grayscale corresponding to the B channel.

[0158] Taking grayscale 160 as an example, for the third test image with grayscale 160 corresponding to the R channel, the R channel value of the red pixel is grayscale 160, the G channel value is grayscale 0, and the B channel value is grayscale 0. For the third test image with grayscale 160 corresponding to the G channel, the G channel value of the green pixel is grayscale 160, the R channel value is grayscale 0, and the B channel value is grayscale 0. For the third test image with grayscale 160 corresponding to the B channel, the B channel value of the blue pixel is grayscale 160, the R channel value is grayscale 0, and the G channel value is grayscale 0.

[0159] S211 , obtaining a third screen brightness of a central area of ​​the display panel when each third test image is displayed.

[0160] The third screen brightness is the brightness of the center of the display panel when the third test image is displayed. The third screen brightness of the third test image with grayscale of 1 to 255 corresponding to the R channel is The measured G channel corresponds to the third screen brightness of the third test image of 1 to 255 gray levels: The measured B channel corresponds to the third screen brightness of the third test image of 1 to 255 gray levels: For the subsequent calculation of the third load intensity, see step S212 below.

[0161] S212. Determine the third load intensity of each third test image corresponding to the R channel, the third load intensity of each third test image corresponding to the G channel, and the third load intensity of each third test image corresponding to the B channel based on the first linear relationship and the third screen brightness.

[0162] Specifically, and Substitute into formula 5 respectively to obtain the third load intensity corresponding to the R channel The third load intensity corresponding to the G channel The third load intensity corresponding to channel B

[0163] S213. Determine the first exponential coefficient of the grayscale influence on the load intensity of the R channel according to the third load intensity of each third test image corresponding to the R channel and the load intensity weight values ​​of the R, G, and B channels; determine the second exponential coefficient of the grayscale influence on the load intensity of the G channel according to the third load intensity of each third test image corresponding to the G channel and the load intensity weight values ​​of the R, G, and B channels; determine the second exponential coefficient of the grayscale influence on the load intensity of the B channel according to the third load intensity of each third test image corresponding to the B channel and the load intensity weight values ​​of the R, G, and B channels.

[0164] The grayscale of the portion outside the central area is k. The relationship between the grayscale k of each R, G, and B sub-channel and the load intensity is shown in the following formula 10:

[0165] in, and is an unknown relationship, but the specific value can be solved by the equation group and recorded as the intermediate variable under the R, G, and B channels respectively. Therefore, for each grayscale k, the corresponding and 0.3 means that the number of white pixels accounts for 30% of the total number of pixels in the third test image.

[0166] Figure 7 is a schematic diagram of a first correlation curve between an intermediate variable and a grayscale variable provided in an embodiment of the present disclosure, Figure 8 is a schematic diagram of a second correlation curve between an intermediate variable and a grayscale variable provided in an embodiment of the present disclosure, and Figure 9 is a schematic diagram of a third correlation curve between an intermediate variable and a grayscale variable provided in an embodiment of the present disclosure.

[0167] Afterwards, for the R channel, according to each grayscale k and the corresponding intermediate variable The numerical value of , fitting to get the intermediate variable The first correlation curve between the grayscale variable k and the grayscale variable k is shown in FIG7 . According to the first correlation curve, the intermediate variable The first exponential coefficient g is derived from the first relational expression between the grayscale variable k and the grayscale variable k (see the following formula 11).R .

[0168] Among them, g R Indicates the exponential coefficient of the red channel grayscale affecting the load intensity I.

[0169] For the G channel, according to the values ​​of each grayscale k and the corresponding intermediate variables, a second correlation curve between the intermediate variables and the grayscale variables is obtained by fitting, as shown in Figure 8. According to the second correlation curve, a second relationship between the intermediate variables and the grayscale variables is obtained (see the following formula 12). According to the second relationship, the second exponential coefficient g is reversely deduced. G .

[0170] Among them, g G Indicates the exponential coefficient of the green channel grayscale's impact on load intensity I.

[0171] For the B channel, according to the values ​​of each grayscale k and the corresponding intermediate variables, a third correlation curve between the intermediate variables and the grayscale variables is obtained by fitting, as shown in Figure 9. According to the third correlation curve, a third relationship between the intermediate variables and the grayscale variables is obtained (see Formula 13 below). According to the third relationship, the third exponential coefficient g is reversely deduced. B .

[0172] Among them, g B Indicates the exponential coefficient of the blue channel grayscale affecting the load intensity I.

[0173] Steps S21 to S213 above are the specific process of determining the load intensity weight value and exponential coefficient. Therefore, after determining the load intensity weight values ​​corresponding to the R, G, and B channels, as well as the first, second, and third exponential coefficients, a first correlation between the load intensity and the grayscale variable of the display panel is established based on the relationship between the load intensity and the grayscale variable as indicated in Formula 10. For details, see Formula 1.

[0174] It can be seen from this that the load intensity is a variable with a value in the interval [0,1]. When the grayscale of all pixels in the display panel is 255, I=1; when the grayscale of all pixels in the display panel is 0, I=0.

[0175] In some embodiments, the step of pre-establishing a second association relationship between the grayscale variable and the brightness includes S31 to S35.

[0176] S31. According to a fourth preset strategy, three fourth test image groups corresponding to the three channels R, G, and B are generated, respectively. The fourth test image groups corresponding to any channel include fourth test image subgroups corresponding to at least some of the grayscales from 0 to 255, each fourth test image subgroup includes m fourth test images, and the display panel is controlled to sequentially display the m fourth test images of each fourth test image subgroup.

[0177] The pixels in the surrounding areas of the 1st to (m-1) / 2nd fourth test images are all the same, the pixels in the surrounding areas of the (m+1) / 2+1st to mth fourth test images are all the same, the surrounding areas of any jth fourth test image are all the same, and the central areas of any jth fourth test image are all the same. 1≤j≤m, j and m are both positive integers, m is an odd number greater than 1 and less than the resolution of the fourth test image. The resolution of the fourth test image is the same as the physical resolution of the display panel.

[0178] For example, for any subset of the fourth test images, the pixels in the surrounding areas of the 1st to (m-1) / 2th fourth test images are black pixels, and the pixels in the surrounding areas of the (m+1) / 2+1st to mth fourth test images are white pixels. The three channel values ​​of black pixels are all 0, and the three channel values ​​of white pixels are all 255.

[0179] It should be noted that the pixels in the surrounding area of ​​the 1st to (m-1) / 2th fourth test images may also be other pixels that are approximately black, for example, pixels whose three channel values ​​are all 1. Similarly, the pixels in the surrounding area of ​​the (m+1) / 2+1st to mth fourth test images may also be other pixels that are approximately white, for example, pixels whose three channel values ​​are all 254. This disclosure uses the example of the pixels in the surrounding area being black pixels and white pixels, respectively.

[0180] For two adjacent fourth test images in any fourth test image subset, the number of pixels in the middle area is different. Exemplarily, for two adjacent fourth test images in any fourth test image subset, the ratio of the number of pixels in the middle area of ​​one fourth test image to the total number of pixels in the fourth test image is a first ratio, and the ratio of the number of pixels in the middle area of ​​the other fourth test image to the total number of pixels in the fourth test image is a second ratio, and the absolute value of the difference between the first ratio and the second ratio is equal. Optionally, for 1 to (m+1) / 2 fourth test images in any fourth test image subset, the difference between the ratio of the number of pixels in the central area of ​​the m'+1th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central area of ​​the m'th fourth test image to the total number of pixels in the fourth test image is equal to a first preset value, and the first preset value is any value selected from 0.1, 0.2, 0.3 or 0.4; m' is a positive integer from 1 to (m+1) / 2-1; for any fourth test image, The (m+1) / 2 to m fourth test images in the four test image subset, wherein the difference between the ratio of the number of pixels in the central area of ​​the m″th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central area of ​​the m″-1th fourth test image to the total number of pixels in the fourth test image is equal to a second preset value, where the second preset value is any value selected from 0.1, 0.2, 0.3, or 0.4; the first preset value is equal to the second preset value; and m″ is a positive integer selected from (m+1) / 2+1 to m.

[0181] Figure 10a is a schematic diagram of the fourth test image subset corresponding to 64 grayscales, 128 grayscales and 255 grayscales corresponding to the R channel provided in an embodiment of the present disclosure, Figure 10b is a schematic diagram of the fourth test image subset corresponding to 64 grayscales, 128 grayscales and 255 grayscales corresponding to the G channel provided in an embodiment of the present disclosure, and Figure 10c is a schematic diagram of the fourth test image subset corresponding to 64 grayscales, 128 grayscales and 255 grayscales corresponding to the B channel provided in an embodiment of the present disclosure. As shown in Figures 10a to 10c, the fourth preset strategy is as follows: take 0.1 as the first preset value and the second preset value, and m takes 19 as an example. For any subset of fourth test images, the pixels in the peripheral areas of the first 1 to 9 fourth test images are black pixels, the number of pixels in the central area of ​​the first fourth test image accounts for 10% of the total number of pixels in the fourth test image; the number of pixels in the central area of ​​the second fourth test image accounts for 20% of the total number of pixels in the fourth test image; the number of pixels in the central area of ​​the third fourth test image accounts for 30% of the total number of pixels in the fourth test image; ...; the number of pixels in the central area of ​​the tenth fourth test image accounts for 100% of the total number of pixels in the fourth test image. The pixels in the peripheral areas of the next 11 to 19 fourth test images are white pixels, the number of pixels in the central area of ​​the 11th fourth test image accounts for 90% of the total number of pixels in the fourth test image; the number of pixels in the central area of ​​the 12th fourth test image accounts for 80% of the total number of pixels in the fourth test image; the number of pixels in the central area of ​​the 13th fourth test image accounts for 70% of the total number of pixels in the fourth test image; ...; the number of pixels in the central area of ​​the 19th fourth test image accounts for 10% of the total number of pixels in the fourth test image.

[0182] The smaller the first and second preset values ​​are, the larger the value of m is, and the more accurate the second correlation relationship obtained in the subsequent calculation is. However, the amount of calculation is large and the efficiency is low. In order to improve efficiency and ensure a certain degree of accuracy, the first and second preset values ​​can be selected as 0.4.

[0183] The pixels of the (m+1) / 2th fourth test image corresponding to the R channel are red pixels, the pixels of the (m+1) / 2th fourth test image corresponding to the G channel are green pixels, and the pixels of the (m+1) / 2th fourth test image corresponding to the B channel are blue pixels.

[0184] The pixels in the middle area of ​​the fourth test image corresponding to the R channel are red pixels. For the fourth test image corresponding to the R channel at grayscale k, the R channel value of the red pixels in the fourth test image is grayscale k, the G channel value is grayscale 0, and the B channel value is grayscale 0.

[0185] The pixels in the middle area of ​​the fourth test image corresponding to the G channel are green pixels. For the fourth test image corresponding to the G channel at grayscale k, the G channel value of the green pixels in the fourth test image is grayscale k, the R channel value is grayscale 0, and the B channel value is grayscale 0.

[0186] The pixels in the middle area of ​​the fourth test image corresponding to the B channel are blue pixels. For the fourth test image corresponding to the B channel at grayscale k, the blue pixels in the fourth test image have a B channel value of grayscale k, an R channel value of grayscale 0, and a G channel value of grayscale 0.

[0187] For each channel, the fourth test image subset corresponding to at least a portion of the grayscales can be, for example, a subset corresponding to a portion of the grayscales from 0 to 255, or a subset corresponding to all grayscales. For each channel, the more fourth test image subsets corresponding to grayscales selected, the more accurate the second association relationship established. However, this also requires a greater computational effort. Therefore, based on actual experience and product requirements, an appropriate number of fourth test image subsets corresponding to grayscales can be selected to establish the second association relationship.

[0188] It should be noted that the selected partial grayscales for at least a portion of the grayscales corresponding to each channel of the fourth test image subset are the same. Exemplarily, the selected partial grayscales may be 16 grayscales, 32 grayscales, 64 grayscales, 96 grayscales, 112 grayscales, 128 grayscales, 144 grayscales, 160 grayscales, 176 grayscales, 192 grayscales, 208 grayscales, 224 grayscales, 240 grayscales, or 255 grayscales. Taking grayscale 160 as an example, for the fourth test image subset with grayscale 160 corresponding to the R channel, the R channel value of the red pixels of each fourth test image in the fourth test image subset is 160 grayscale, the G channel value is 0 grayscale, and the B channel value is 0 grayscale. For the fourth test image subset with grayscale 160 corresponding to the G channel, the G channel value of the green pixels of each fourth test image in the fourth test image subset is 160 grayscale, the R channel value is 0 grayscale, and the B channel value is 0 grayscale. For the fourth test image subset with grayscale 160 corresponding to the B channel, the B channel values ​​of the blue pixels in the fourth test image subset are all grayscale 160, the R channel values ​​are all grayscale 0, and the G channel values ​​are all grayscale 0.

[0189] S32. Obtain a fourth screen brightness of the middle area of ​​the display panel when each fourth test image is displayed.

[0190] The fourth screen brightness is the brightness of the screen center of the display panel measured by the CA410 color analyzer when the fourth test image is displayed.

[0191] FIG11 is a schematic diagram of data of the fourth screen brightness at some grayscales extracted according to an embodiment of the present disclosure. As shown in FIG11 , the R, G, and B channels correspond to the fourth screen brightness at some grayscales, respectively. The grayscales include 16, 32, 64, 96, 112, 128, 144, 160, 176, 192, 208, 224, 240, and 255.

[0192] S33. For any grayscale k, determine the first theoretical brightness corresponding to the minimum load intensity and the second theoretical brightness corresponding to the maximum load intensity based on the fourth screen brightness of the m fourth test images and the ratio of the number of pixels in the central area of ​​the m fourth test images to the total number of pixels in the fourth test images shown.

[0193] Here, k takes any value selected from at least a portion of the grayscales from 0 to 255.

[0194] The minimum load intensity is I=0; the maximum load intensity is I=1.

[0195] Figure 12 is a line graph of 19 fourth test images-fourth screen brightness provided in an embodiment of the present disclosure. As shown in Figure 12, the horizontal axis represents the position of the fourth test image in a group of fourth test image subgroups, and the vertical axis represents the fourth screen brightness corresponding to the fourth test image. Taking the first and second preset values ​​as 0.1 and m as 19 as an example, for any grayscale k=255, combined with the data analysis in Figure 10, a line graph of the 19 fourth test images and the fourth screen brightness is obtained. As shown in Figure 12, the ratio of the number of pixels in the central area of ​​the first 10 fourth test images to the total number of pixels in the fourth test image is arithmetically distributed, and the ratio of the number of pixels in the central area of ​​the last 10 fourth test images to the total number of pixels in the fourth test image is arithmetically distributed. The corresponding fourth screen brightness of the first 10 fourth test images is fitted to conform to a linear relationship, and the maximum fourth screen brightness corresponding to the minimum load intensity I=0 is deduced as the first theoretical brightness L0; similarly, the corresponding fourth screen brightness of the last 10 fourth test images is fitted to conform to a linear relationship, and the minimum fourth screen brightness corresponding to the maximum load intensity I=1 is deduced as the second theoretical brightness L1, thereby obtaining the table shown in Figure 13. Figure 13 is a data schematic diagram of the first theoretical brightness and the second theoretical brightness under the grayscale corresponding to the RGB three channels provided by the embodiment of the present disclosure.

[0196] S34. For each of the three channels R, G, and B, according to each grayscale and the second theoretical brightness at each grayscale, fit the second gamma curve under the maximum load intensity to obtain an expression of the second gamma curve and determine the second gamma value.

[0197] For the R channel, according to each grayscale and the second theoretical brightness at each grayscale, the second Gamma curve at the maximum load intensity I=1 is fitted to obtain an expression of the second Gamma curve, as shown in the following formula 14.

[0198] in, Indicates the second theoretical brightness of the R channel k grayscale when I = 1; Indicates the second theoretical brightness of the R channel 255 grayscale when I=1; Indicates the index parameter to be determined for the R channel. The specific value is the second Gamma value corresponding to the R channel.

[0199] Afterwards, the exponential parameter, that is, the second Gamma value corresponding to the R channel, is reversely derived according to Formula 14.

[0200] For the G channel, according to each grayscale and the second theoretical brightness at each grayscale, a second Gamma curve at the maximum load intensity I=1 is fitted to obtain an expression of the second Gamma curve, as shown in the following formula 15.

[0201] in, Indicates the second theoretical brightness of the G channel k grayscale when I = 1; Indicates the second theoretical brightness of the G channel 255 grayscale when I=1; Indicates the exponential parameter to be determined for the G channel. The specific value of is the second Gamma value corresponding to the G channel.

[0202] Afterwards, the exponential parameter, that is, the second Gamma value corresponding to the G channel, is reversely derived according to Formula 17.

[0203] For the B channel, according to each grayscale and the second theoretical brightness at each grayscale, the second Gamma curve at the maximum load intensity I=1 is fitted to obtain an expression of the second Gamma curve, as shown in the following formula 16.

[0204] in, Indicates the second theoretical brightness of the B channel k grayscale when I = 1; Indicates the second theoretical brightness of the B channel 255 grayscale when I=1; Indicates the index parameter to be determined for channel B. The specific value is the second Gamma value corresponding to the B channel.

[0205] Afterwards, the exponential parameter, that is, the second Gamma value corresponding to the B channel, is reversely derived according to Formula 18.

[0206] S35 . Determine a second association relationship according to the expressions indicated by the second gamma curves corresponding to the three channels R, G, and B, respectively, and the second gamma value.

[0207] Using Formulas 15 to 16 above, combined with the derived second gamma values ​​corresponding to the R, G, and B channels, a second correlation is determined, as shown in Formula 2. That is, the second correlation between the grayscale variable and brightness follows the second gamma curve distribution at the maximum load intensity I = 1.

[0208] In some embodiments, the step of pre-establishing a third correlation relationship between the grayscale variable, the load intensity, and the brightness of the display panel includes S41 to S43.

[0209] S41. For each of the three channels R, G, and B, a first gamma curve under minimum load intensity is fitted according to each grayscale and the first theoretical brightness under each grayscale to obtain an expression of the first gamma curve and determine a first gamma value.

[0210] For the R channel, according to each grayscale and the first theoretical brightness under each grayscale, the first Gamma curve under the minimum load intensity I=0 is fitted to obtain the expression indicated by the first Gamma curve, see the following formula 17.

[0211] in, Indicates the first theoretical brightness of the R channel k grayscale when I = 0; Indicates the first theoretical brightness of the R channel 255 grayscale when I = 0; Indicates the index parameter to be determined when I=0 for the R channel. The specific value of is the first Gamma value corresponding to the R channel.

[0212] Afterwards, the exponential parameter, that is, the first Gamma value corresponding to the R channel, is reversely derived according to Formula 19.

[0213] For the G channel, according to each grayscale and the first theoretical brightness under each grayscale, a first Gamma curve under the minimum load intensity I=0 is fitted to obtain an expression indicated by the first Gamma curve, see the following formula 18.

[0214] in, Indicates the first theoretical brightness of the G channel k grayscale when I = 0; Indicates the first theoretical brightness of the G channel 255 grayscale when I = 0; Indicates the exponential parameter to be determined for the G channel when I=0. The specific value of is the first Gamma value corresponding to the G channel.

[0215] Afterwards, the exponential parameter, that is, the first Gamma value corresponding to the G channel, is reversely derived according to Formula 20.

[0216] For the B channel, according to each grayscale and the first theoretical brightness under each grayscale, the first Gamma curve under the minimum load intensity I=0 is fitted to obtain the expression indicated by the first Gamma curve, see the following formula 19.

[0217] in, Indicates the first theoretical brightness of the B channel k grayscale when I = 0; Indicates the first theoretical brightness of the B channel 255 grayscale when I = 0; Indicates the index parameter to be determined for channel B when I=0. The specific value of is the first Gamma value corresponding to the B channel.

[0218] Afterwards, the exponential parameter, that is, the first Gamma value corresponding to the B channel, is reversely derived according to Formula 21.

[0219] S42 , fitting the second linear relationship between load intensity and brightness corresponding to the three channels R, G, and B at the k grayscale based on the linear characteristics of load intensity and brightness, the first theoretical brightness at the k grayscale, and the second theoretical brightness.

[0220] It is known that when the grayscale is fixed, the brightness changes linearly with the load intensity. Figure 14 is a schematic diagram of the second linear relationship between load intensity and brightness estimated according to the first theoretical brightness and the second theoretical brightness at the k grayscale according to the embodiment of the present disclosure. As shown in Figure 14, according to the linear characteristics of load intensity and brightness, the first theoretical brightness L0(k) and the second theoretical brightness L1(k) at the k grayscale can be fitted to obtain the brightness estimation curve shown in Figure 14, that is, the second linear relationship corresponding to a certain channel (any one of R, G, and B) at the k grayscale. Among them, the second linear relationship between load intensity and brightness corresponding to the R channel at the k grayscale, see the following formula 20. The second linear relationship between load intensity and brightness corresponding to the G channel at the k grayscale, see the following formula 21. The second linear relationship between load intensity and brightness corresponding to the B channel at the k grayscale, see the following formula 22.

[0221] S43. Determine a third association relationship corresponding to the R, G, and B channels at grayscale k based on a second linear relationship between load intensity and brightness corresponding to the R, G, and B channels, and an expression of a first gamma curve and an expression of a second gamma curve corresponding to the R, G, and B channels at grayscale k.

[0222] Given the second linear relationship (Formula 20 to Formula 22), the expression of the first Gamma curve (Formula 17 to Formula 19), and the expression of the second Gamma curve (Formula 14 to Formula 16), substitute Formula 14 and Formula 17 into Formula 20 to obtain the actual brightness expression corresponding to the R channel, see the following Formula 23; substitute Formula 15 and Formula 18 into Formula 21 to obtain the actual brightness expression corresponding to the G channel, see the following Formula 24; substitute Formula 16 and Formula 19 into Formula 22 to obtain the actual brightness expression corresponding to the B channel, see the following Formula 25.

[0223] in, and They represent the actual brightness corresponding to the R, G, and B channels under (k, I) respectively.

[0224] The main idea of ​​grayscale (or brightness) compensation for the display panel is to first find a compensation grayscale k' that is smaller than the current grayscale k R , so that it satisfies Expand and substitute into Formula 23, Formula 24, and Formula 25 to obtain the following equation group (1):

[0225] Assumptions Substituting it into the above equation group (1) we can get the following equation group (2):

[0226] According to equation group (2), I′ can be replaced by the known approximate value I, thereby determining the third relationship:

[0227] in, These are all known numbers calculated using the previous method.

[0228] FIG15 is a schematic diagram of a specific process of grayscale compensation provided by an embodiment of the present disclosure. As shown in FIG15 , first, by analyzing the characteristics of the display panel, a first correlation relationship, a second correlation relationship, and a third correlation relationship are established. The establishment of the first correlation relationship specifically includes constructing a curve of the relationship between W255 grayscale brightness and opr to obtain a first linear relationship; calculating the load intensity weight value w of the three channels R, G, and B that affects the load intensity I R 、w G 、w B ; Calculate the exponential coefficient g of the grayscale of the three channels R, G, and B that affects the load intensity I R 、g G and g B ; Determine the calculation formula for load intensity I (see formula 1). The process of establishing the second association relationship and the third association relationship specifically includes calculating the first theoretical brightness and the second theoretical brightness of RGB255 grayscale when I=0 and I=1; fitting the first Gamma curve and the second Gamma curve, calculating the Gamma value of RGB when I=0 and I=1, that is, determining the first Gamma value and And the second Gamma value and Determine a calculation formula for target brightness information (see Formula 2), and determine a third association relationship (see Formula 3).

[0229] In the actual compensation process, the channel value of the R channel, the channel value of the G channel, the channel value of the B channel and the actual load intensity I of each pixel in the image to be displayed are substituted into Formula 3, and L R (k,I) is equal to the brightness data indicated by the target brightness information under the R channel Let L G (k,I) is equal to the brightness data indicated by the target brightness information under the G channel Let L B (k,I) is equal to the brightness data indicated by the target brightness information under the B channel Refer to the following equation group (3) to finally solve the k′ after the pixel R, G, and B channels are compensated R , k′ G and k′ B .

[0230] Those skilled in the art will understand that in the above-mentioned method of the specific implementation method, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0231] In addition, embodiments of the present disclosure also provide a grayscale compensation device corresponding to the grayscale compensation method, configured to implement the grayscale compensation method. Because the principles underlying the problem solved by the device in the embodiments of the present disclosure are similar to those of the grayscale compensation method in the embodiments of the present disclosure, the implementation of the device can be referenced to the implementation of the method, and any repetitions will not be repeated.

[0232] The grayscale compensation device includes a storage module and a grayscale compensation module. The storage module is configured to store pre-established first, second, and third association relationships: the first association relationship is the association relationship between the load intensity of the display panel and the grayscale variable; the second association relationship is the association relationship between the grayscale variable and the brightness; and the third association relationship is the association relationship between the grayscale variable, the load intensity, and the brightness of the display panel.

[0233] The grayscale compensation module is configured to acquire multiple frames of images to be displayed, and for each frame of the image to be displayed, determine the actual load intensity corresponding to the image to be displayed based on the initial grayscale data and pixel position information of each pixel point in the image to be displayed, using a pre-established first association relationship; determine the target brightness information corresponding to each pixel point based on the initial grayscale data of each pixel point in the image to be displayed, using a pre-established second association relationship; and determine the compensated grayscale data of each pixel point after compensation based on the initial grayscale data, actual load intensity and target brightness information of each pixel point in the image to be displayed, using a pre-established third association relationship.

[0234] Exemplarily, the grayscale compensation module may be a field programmable gate array (FPGA).

[0235] The disclosed embodiments pre-establish a relationship model between grayscale, load intensity, and brightness, namely, a first correlation, a second correlation, and a third correlation. Based on the relationship model, a compensation algorithm for a specific grayscale under a specific load intensity is designed, ultimately achieving consistent brightness of the same grayscale under different voltage drop levels. The disclosed embodiments employ an external compensation method, which uses an external device to sense the optical characteristics of pixels and construct a relationship model between grayscale, load intensity, and brightness, thereby achieving grayscale compensation. This method is simple, has a fast drive speed, and a wider compensation range.

[0236] In addition, an embodiment of the present disclosure further provides a display device. FIG16 is a schematic diagram of the display device provided by the embodiment of the present disclosure. As shown in FIG16 , the display device includes a grayscale compensation device 51 and a display panel 52. The grayscale compensation device 51 is configured to store a pre-established first association relationship, a second association relationship, and a third association relationship; the first association relationship is the association relationship between the load intensity of the display panel and the grayscale variable; the second association relationship is the association relationship between the grayscale variable and the brightness; and the third association relationship is the association relationship between the grayscale variable, the load intensity, and the brightness of the display panel; and obtain multiple frames of images to be displayed, and for each frame of the image to be displayed, determine the actual load intensity corresponding to the image to be displayed based on the initial grayscale data and pixel position information of each pixel in the image to be displayed using the pre-established first association relationship; determine the target brightness information corresponding to each pixel based on the initial grayscale data of each pixel in the image to be displayed using the pre-established second association relationship; and determine the compensated grayscale data of each pixel after compensation based on the initial grayscale data, the actual load intensity, and the target brightness information of each pixel in the image to be displayed using the pre-established third association relationship, and send the compensated grayscale data to the display panel 52. The display panel 52 is configured to display each frame of the image to be displayed according to the corresponding compensated grayscale data.

[0237] The disclosed embodiments pre-establish a relationship model between grayscale, load intensity, and brightness, namely, first, second, and third associations. Based on these relationships, a compensation algorithm for a specific grayscale under a specific load intensity is designed, ultimately achieving consistent brightness for the same grayscale under different voltage drop levels. By using an external device to sense the optical characteristics of pixels and constructing a relationship model between grayscale, load intensity, and brightness, the disclosed embodiments achieve grayscale compensation with a simple compensation method, fast drive speed, and a wider compensation range.

[0238] Figure 17 is a schematic diagram of the structure of a computer device provided in an embodiment of the present disclosure. As shown in Figure 17, the computer device provided in an embodiment of the present disclosure includes: one or more processors 601, memory 602, and one or more I / O interfaces 603. The memory 602 stores one or more programs. When executed by the one or more processors, the one or more processors implement any of the grayscale compensation methods described in the above embodiments. The one or more I / O interfaces 603 are connected between the processors and the memory and are configured to facilitate information exchange between the processors and the memory.

[0239] Among them, the processor 601 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 602 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read-write interface) 603 is connected between the processor 601 and the memory 602, and can realize information interaction between the processor 601 and the memory 602, including but not limited to a data bus (Bus), etc.

[0240] In some embodiments, the processor 601 , the memory 602 , and the I / O interface 603 are connected to each other via a bus 604 , and further connected to other components of the computing device.

[0241] According to an embodiment of the present disclosure, a non-transitory computer-readable storage medium is further provided, wherein the non-transitory computer-readable storage medium stores a computer program, wherein when the program is executed by a processor, the steps of the grayscale compensation method in any of the above embodiments are implemented.

[0242] In particular, 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 machine-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above-mentioned functions defined in the system of the present disclosure are executed.

[0243] It should be noted that the computer non-transitory readable medium shown in the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media can 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium can 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 the present disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any non-transitory computer-readable storage 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 non-transitory computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination thereof.

[0244] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architectures, functions and operations of the devices, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the aforementioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two connected boxes can actually represent execution in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0245] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present disclosure, and such modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A grayscale compensation method, applied to the display of a display panel, wherein, The grayscale compensation method includes: acquiring multiple frames of images to be displayed, and performing grayscale compensation on the images to be displayed to obtain compensated grayscale data after compensation; The performing grayscale compensation on the images to be displayed to obtain compensated grayscale data after compensation includes: According to the initial grayscale data and pixel position information of each pixel point in the images to be displayed, using a pre-established first correlation relationship, determining the actual load intensity corresponding to the images to be displayed; the first correlation relationship is the correlation relationship between the load intensity of the display panel and the grayscale variable; According to the initial grayscale data of each pixel point in the images to be displayed, using a pre-established second correlation relationship, determining the target brightness information corresponding to each pixel point; the second correlation relationship is the correlation relationship between the grayscale variable and the brightness; According to the initial grayscale data of each pixel point in the images to be displayed, the actual load intensity, and the target brightness information, using a pre-established third correlation relationship, determining the compensated grayscale data after compensation for each of the pixel points, the third correlation relationship is the correlation relationship between the grayscale variable, the load intensity, and the brightness of the display panel.

2. The grayscale compensation method according to claim 1, wherein, It further includes the step of pre-establishing the first correlation relationship between the load intensity of the display panel and the grayscale variable, including: According to the pre-determined load intensity weight values of the red R, green G, and blue B channels, and the first exponential coefficient, second exponential coefficient, and third exponential coefficient of the grayscale affecting the load intensity corresponding to the R, G, and B channels respectively, establishing the first correlation relationship between the load intensity of the display panel and the grayscale variable.

3. The grayscale compensation method according to claim 2, wherein, Before determining the load intensity weight values of the R, G, and B channels, it further includes: Generating n first test images according to a first preset strategy, and controlling the display panel to display; each of the first test images includes white pixels, and the number of white pixels in the i-th first test image accounts for i / n of the total number of pixels in the i-th first test image, 1 ≤ i ≤ n, i is a positive integer, n is a positive integer greater than 1, and n is less than or equal to the resolution of the first test image rate; Acquiring the first screen brightness of the white pixel aggregation area in the display panel when each of the first test images is displayed; For the i-th first test image, taking the ratio of the number of white pixels to the total number of pixels therein as the first load intensity of the i-th first test image; According to the first screen brightness and the first load intensity corresponding to each of the first test images, fitting to obtain the first linear relationship between the load intensity and the screen brightness.

4. The grayscale compensation method according to claim 3, wherein It further includes the step of determining the load intensity weight values of the R, G, and B channels, including: Generate second test images corresponding to the R, G, and B channels respectively according to the second preset strategy, and control the display panel to display; the second test image corresponding to the R channel includes white pixels in the first intermediate area and red pixels in the first surrounding area, the second test image corresponding to the G channel includes white pixels in the second intermediate area and green pixels in the second surrounding area, and the second test image corresponding to the B channel includes white pixels in the third intermediate area and blue pixels in the third surrounding area; the pixel positions of the white pixels in each of the second test images are the same; Obtain the second screen brightness of the intermediate area of the display panel when each of the second test images is displayed; Determine the second load intensities corresponding to the 3 second test images respectively according to the first linear relationship and the second screen brightness, and use them as the second load intensities corresponding to the R, G, and B channels respectively; According to the second load intensity corresponding to the R channel and the predefined association relationship between the R channel load intensity and the weights of the load intensities of each channel, the load intensity corresponding to the G channel and the predefined association relationship between the G channel load intensity and the weights of the load intensities of each channel, the load intensity corresponding to the B channel and the predefined association relationship between the B channel load intensity and the weights of the load intensities of each channel, and the association relationship between the load intensity weights corresponding to the R, G, and B channels respectively, determine the load intensity weight values of the R, G, and B channels.

5. The grayscale compensation method according to claim 4, wherein, For the second test image corresponding to the R channel, the three-channel values of the white pixels are all 255 gray levels, the R channel value of the red pixels is 255 gray levels, the G channel value is 0 gray levels, and the B channel value is 0 gray levels; For the second test image corresponding to the G channel, the three-channel values of the white pixels are all 255 gray levels, the G channel value of the green pixels is 255 gray levels, the R channel value is 0 gray levels, and the B channel value is 0 gray levels; For the second test image corresponding to the B channel, the three-channel values of the white pixels are all 255 gray levels, the B channel value of the green pixels is 255 gray levels, the R channel value is 0 gray levels, and the G channel value is 0 gray levels.

6. The grayscale compensation method according to claim 4, wherein It also includes the steps of determining the first exponential coefficient, the second exponential coefficient, and the third exponential coefficient, including: Generate third test images corresponding to at least some gray levels of the R, G, and B channels respectively according to a third preset strategy, and control the display panel to display; the third test images corresponding to at least some gray levels of the R channel include white pixels located in a fourth intermediate area and red pixels located in a fourth surrounding area, and the gray levels of the red pixels in different third test images are different; the third test images corresponding to at least some gray levels of the G channel include white pixels located in a fifth intermediate area and green pixels located in a fifth surrounding area, and the gray levels of the green pixels in different third test images are different; the third test images corresponding to at least some gray levels of the B channel include white pixels located in a sixth intermediate area and blue pixels located in a sixth surrounding area, and the gray levels of the blue pixels in different third test images are different; the pixel positions of the white pixels in each third test image are the same; Obtain the third screen brightness of the intermediate area of the display panel when each third test image is displayed; Determine the third load intensity of each third test image corresponding to the R channel, the third load intensity of each third test image corresponding to the G channel, and the third load intensity of each third test image corresponding to the B channel according to the first linear relationship and the third screen brightness; Determine a first exponential coefficient of the gray level of the R channel affecting the load intensity according to the third load intensity of each third test image corresponding to the R channel and the load intensity weight values of the R, G, and B channels; Determine a second exponential coefficient of the gray level of the G channel affecting the load intensity according to the third load intensity of each third test image corresponding to the G channel and the load intensity weight values of the R, G, and B channels; determine a second exponential coefficient of the gray level of the B channel affecting the load intensity according to the third load intensity of each third test image corresponding to the B channel and the load intensity weight values of the R, G, and B channels.

7. The grayscale compensation method according to claim 6, wherein, For each third test image corresponding to the R channel, the three-channel values of the white pixels are all 255 gray levels, and the R-channel values of the red pixels in multiple third test images include at least some gray levels from 0 to 255, the G-channel value is 0 gray level, and the B-channel value is 0 gray level; For each third test image corresponding to the G channel, the three-channel values of the white pixels are all 255 gray levels, and the G-channel values of the red pixels in multiple third test images include at least some gray levels from 0 to 255, the R-channel value is 0 gray level, and the B-channel value is 0 gray level; For each third test image corresponding to the B channel, the three-channel values of the white pixels are all 255 gray levels, and the B-channel values of the red pixels in multiple third test images include at least some gray levels from 0 to 255, the R-channel value is 0 gray level, and the G-channel value is 0 gray level; At least some gray levels from 0 to 255 included in the R-channel value, at least some gray levels from 0 to 255 included in the G-channel value, and at least some gray levels from 0 to 255 included in the B-channel value are the same.

8. The grayscale compensation method according to claim 1, wherein, It also includes the step of pre-establishing a second correlation relationship between the gray level variable and the brightness, including: According to the fourth preset strategy, generate three groups of fourth test image groups corresponding to the R, G, and B channels respectively. Each group of fourth test image groups corresponding to any channel includes fourth test image subgroups corresponding to at least some gray levels from 0 to 255. Each group of the fourth test image subgroups includes m fourth test images. Control the display panel to sequentially display the m fourth test images of each group of fourth test image subgroups; wherein, the pixels in the surrounding areas of the first to (m - 1) / 2 fourth test images are the same, the pixels in the surrounding areas of the (m + 1) / 2 + 1 to m fourth test images are the same, and the pixels in the surrounding areas of any j-th fourth test image are the same, 1 ≤ j ≤ m, both j and m are positive integers, m is an odd number greater than 1 and less than the resolution of the fourth test image; the pixels in the middle area of the fourth test image corresponding to the R channel are red pixels; the pixels in the middle area of the fourth test image corresponding to the G channel are green pixels; the pixels in the middle area of the fourth test image corresponding to the B channel are blue pixels; for two adjacent fourth test images in any of the fourth test image subgroups, the number of pixels in the middle area is different; the pixels of the (m + 1) / 2-th fourth test image corresponding to the R channel are red pixels, the pixels of the (m + 1) / 2-th fourth test image corresponding to the G channel are green pixels, and the pixels of the (m + 1) / 2-th fourth test image corresponding to the B channel are blue pixels; Obtain the fourth screen brightness of the middle area of the display panel when each of the fourth test images is displayed; For any gray level k, determine the second theoretical brightness corresponding to the maximum load intensity according to the fourth screen brightness of the m fourth test images and the ratio of the number of pixels in the central area of the m fourth test images to the total number of pixels in the shown fourth test image; k takes any value from at least some gray levels selected from 0 to 255 gray levels; For each of the R, G, and B channels, according to each gray level and the second theoretical brightness at each gray level, fit the second Gamma curve under the maximum load intensity, obtain the expression of the second Gamma curve, and determine the second Gamma value; According to the expressions indicated by the second Gamma curves corresponding to the R, G, and B channels respectively and the second Gamma value, determine the second correlation relationship. It further includes the step of pre-establishing the third correlation relationship between the gray level variable, the load intensity, and the brightness of the display panel, including:

9. The grayscale compensation method according to claim 8, wherein, For any gray level k, determine the first theoretical brightness corresponding to the minimum load intensity according to the fourth screen brightness of the m fourth test images and the ratio of the number of pixels in the central area of the m fourth test images to the total number of pixels in the shown fourth test image; For each of the R, G, and B channels, according to each gray level and the first theoretical brightness at each gray level, fit the first Gamma curve under the minimum load intensity, obtain the expression of the first Gamma curve, and determine the first Gamma value; ​ According to the linear characteristics of the load intensity and the brightness, the first theoretical brightness and the second theoretical brightness at the k gray level are used to fit and obtain the second linear relationship between the load intensity and the brightness corresponding to the R, G, and B channels respectively at the k gray level; According to the second linear relationship between the load intensity and the brightness corresponding to the R, G, and B channels respectively at the k gray level, the expressions of the first Gamma curve and the second Gamma curve corresponding to the R, G, and B channels respectively at the k gray level, the actual brightness expressions corresponding to the R, G, and B channels respectively at the k gray level are determined; According to the actual brightness expressions corresponding to the R, G, and B channels respectively at the k gray level, and the assumed compensated gray level data k′ (k′ is less than k), a third correlation relationship corresponding to the R, G, and B channels respectively at the k gray level is established; 10. The grayscale compensation method according to claim 9, wherein, The compensated gray level data of each pixel point after compensation is determined by using the pre-established third correlation relationship according to the initial gray level data, the actual load intensity, and the target brightness information of each pixel point in the to-be-displayed image, including: Substituting the initial gray level data, the actual load intensity, and the target brightness information of each pixel point into the expression indicated by the third correlation relationship, and calculating the compensated gray level data k′ of each pixel point after compensation.

11. The grayscale compensation method according to claim 8, wherein, For any set of fourth test image subgroups, among the first to (m - 1) / 2 fourth test images, the pixels in the surrounding area are black pixels, and among the (m + 1) / 2 + 1 to m fourth test images, the pixels in the surrounding area are white pixels.

12. The grayscale compensation method according to claim 11, wherein, For the fourth test image corresponding to the R channel at the k gray level, the R channel value of the red pixel is the k gray level, the G channel value is the 0 gray level, and the B channel value is the 0 gray level; For the fourth test image corresponding to the G channel at the k gray level, the G channel value of the green pixel is the k gray level, the R channel value is the 0 gray level, and the B channel value is the 0 gray level; For the fourth test image corresponding to the B channel at the k gray level, the B channel value of the blue pixel is the k gray level, the R channel value is the 0 gray level, and the G channel value is the 0 gray level.

13. The grayscale compensation method according to claim 12, wherein, For the first to (m + 1) / 2 fourth test images in any of the fourth test image subgroups, the difference between the ratio of the number of pixels in the central area of the (m′ + 1)-th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central area of the m′-th fourth test image to the total number of pixels in the fourth test image is equal to a first preset value, and the first preset value takes any value among 0.1, 0.2, 0.3, or 0.4; m′ takes a positive integer from 1 to (m + 1) / 2 - 1; For (m + 1) / 2 to m fourth test images in any of the fourth test image subgroups, the difference between the ratio of the number of pixels in the central region of the m''-th fourth test image to the total number of pixels in the fourth test image and the ratio of the number of pixels in the central region of the (m'' - 1)-th fourth test image to the total number of pixels in the fourth test image is equal to a second preset value, where the second preset value takes any value of 0.1, 0.2, 0.3, or 0.4; the first preset value is equal to the second preset value; m'' takes a positive integer from (m + 1) / 2 + 1 to m.

14. A grayscale compensation device, wherein, Comprising a storage module and a grayscale compensation module; The storage module is configured to store a pre-established first association relationship, a second association relationship, and a third association relationship; the first association relationship is the association relationship between the load intensity of the display panel and the grayscale variable; the second association relationship is the association relationship between the grayscale variable and the brightness; the third association relationship is the association relationship between the grayscale variable, the load intensity, and the brightness of the display panel; The grayscale compensation module is configured to obtain multiple frames of images to be displayed, and for each frame of the images to be displayed, determine the actual load intensity corresponding to the image to be displayed according to the initial grayscale data and pixel position information of each pixel point in the image to be displayed, using the pre-established first association relationship; determine the target brightness information corresponding to each pixel point according to the initial grayscale data of each pixel point in the image to be displayed, using the pre-established second association relationship; and determine the compensated grayscale data of each pixel point after compensation according to the initial grayscale data, the actual load intensity, and the target brightness information of each pixel point in the image to be displayed, using the pre-established third association relationship.

15. A display device, comprising a grayscale compensation device and a display panel; The grayscale compensation module is configured to store a pre-established first association relationship, a second association relationship, and a third association relationship; the first association relationship is the association relationship between the load intensity of the display panel and the grayscale variable; the second association relationship is the association relationship between the grayscale variable and the brightness; the third association relationship is the association relationship between the grayscale variable, the load intensity, and the brightness of the display panel; And, obtaining multiple frames of images to be displayed, and for each frame of the images to be displayed, determining the actual load intensity corresponding to the image to be displayed according to the initial grayscale data and pixel position information of each pixel point in the image to be displayed, using the pre-established first association relationship; determining the target brightness information corresponding to each pixel point according to the initial grayscale data of each pixel point in the image to be displayed, using the pre-established second association relationship; and determining the compensated grayscale data of each pixel point after compensation according to the initial grayscale data, the actual load intensity, and the target brightness information of each pixel point in the image to be displayed, using the pre-established third association relationship; The display panel is configured to display each frame of the images to be displayed according to the compensated grayscale data corresponding thereto.

16. A computer device, wherein, Including: A processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor. When the computer device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the grayscale compensation method according to any one of claims 1 to 13 are executed.

17. A computer non-transitory readable storage medium, wherein, A computer program is stored on the computer non-transitory readable storage medium, and when the computer program is run by a processor, it executes the steps of the grayscale compensation method described in any one of claims 1 to 13.

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