Color alignment correction method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a color alignment correction method and device of display equipment, electronic equipment and a storage medium, and belongs to the technical field of color alignment correction. The method comprises the following steps: acquiring a target color output value corresponding to a target color input value, and adjusting the target color output value according to a preset fluctuation range to obtain multiple groups of color output values to be selected; wherein the target color is represented by adopting a first color space, and the target color input value is selected according to a first sampling difference value; obtaining color deviation values of the to-be-selected color output values when the to-be-selected color output values are displayed on the display equipment, and determining an optimal value from the multiple color deviation values; and updating the target color output value by adopting the to-be-selected color output value corresponding to the optimal value. Poor gray scale transition can be avoided, and the display effect of the display equipment is improved.

Description

Technical Field

[0001] This application relates to the field of color calibration, and more particularly to a color calibration method, apparatus, electronic device and storage medium. Background Technology

[0002] With the advancement of technology, people have increasingly higher requirements for visual experience, and the color performance of various display devices has become an increasingly important factor in judging the quality of display devices.

[0003] Different display devices typically exhibit different color performances, and even the same display device may develop different color performances over time. To ensure that the color performance of a display device meets certain standards, color accuracy calibration can be performed on the display device.

[0004] When using existing methods to perform color accuracy calibration on display devices, there is a problem with poor grayscale transition, which affects the user's visual experience. Summary of the Invention

[0005] This application provides a color accuracy correction method, apparatus, electronic device, and storage medium, which can solve the problem of poor grayscale transition. The technical solution provided by this application is as follows:

[0006] In a first aspect, embodiments of this application provide a color accuracy calibration method for a display device, including:

[0007] Obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to a preset fluctuation range to obtain multiple sets of candidate color output values; wherein, the target color input value is selected according to a first sampling difference, and the target color is represented using a first color space;

[0008] Obtain the color deviation value when each of the candidate color output values ​​is displayed on the display device, and determine the optimal value from the plurality of color deviation values;

[0009] The target color output value is updated using the candidate color output value corresponding to the optimal value.

[0010] Secondly, embodiments of this application provide a color calibration device for a display device, comprising:

[0011] The fine-tuning module is used to obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to a preset fluctuation range to obtain multiple sets of candidate color output values; wherein, the target color input value is selected according to a first sampling difference, and the target color is represented using a first color space;

[0012] The selection module is used to obtain the color deviation value when each of the candidate color output values ​​is displayed on the display device, and to determine the optimal value from the multiple color deviation values.

[0013] The update module is used to update the target color output value using the candidate color output value corresponding to the optimal value.

[0014] Thirdly, embodiments of this application provide an electronic device, including: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed as described in the first aspect.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the color calibration method as described in the first aspect.

[0016] In this embodiment, multiple sets of candidate color output values ​​are obtained by fine-tuning the values ​​of each color channel in the target color output value according to a certain fluctuation range. Then, the color deviation values ​​corresponding to the multiple sets of candidate color output values ​​are obtained, and the optimal color deviation value is selected from them. The target color output value is replaced with the candidate color output value corresponding to the color deviation value. In this way, fine-tuning the target color output value can hardly affect the color accuracy of the image. Furthermore, after obtaining multiple candidate color output values, the color output value with the best grayscale performance can be determined based on the color deviation value, thereby avoiding the appearance of red and green intermingling in the grayscale, making the grayscale transition more uniform, and improving the user's viewing experience.

[0017] Furthermore, by increasing the sampling grayscale chart according to the second sampling difference (e.g., step size 16), the target color output value corresponding to each grayscale level can be sampled and color accuracy corrected at smaller intervals. This, in turn, allows for more accurate capture of the display's color performance in various brightness areas, resulting in smoother brightness transitions between grayscale levels, thereby improving the overall accuracy of color reproduction and the level of image detail.

[0018] Furthermore, increasing the number of gray levels only within the preset grayscale range has two advantages. First, it allows for more detailed color accuracy correction within the preset grayscale range, which is more prone to poor grayscale transitions, resulting in smoother brightness transitions between adjacent grayscale levels. Second, compared to increasing the number of grayscale levels across the entire range, i.e., increasing the number of sampled grayscale levels across the entire grayscale range, it significantly reduces the computational load of color accuracy correction, lowers the computational burden on the color accuracy correction device, and improves the speed of color accuracy correction.

[0019] Furthermore, when selecting the optimal value from multiple color deviation values, the value with the smallest difference from 0 can be determined as the optimal value, resulting in better color display accuracy. Alternatively, the smallest non-negative value can be determined as the optimal value. In this case, the displayed color will have a yellowish-green tint. When the smallest non-negative value is selected, the color accuracy after correction is closer to the color temperature of natural light, generally providing a more comfortable visual experience. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic flowchart illustrating a color calibration method provided in an embodiment of this application;

[0022] Figure 2 A schematic flowchart illustrating another color calibration method provided in an embodiment of this application;

[0023] Figure 3A An X-ray data curve of a single-channel graphics card and a grayscale graphics card provided in this application embodiment;

[0024] Figure 3B A Y-data curve diagram of a single-channel graphics card and a grayscale graphics card provided in this application embodiment;

[0025] Figure 3C Z-data curves of a single-channel graphics card and a grayscale graphics card provided in this application embodiment;

[0026] Figure 4A An X-ray data curve of a normalized single-channel image card and a grayscale image card provided in this application embodiment;

[0027] Figure 4B A normalized Y-data curve of a single-channel image card and a grayscale image card is provided for embodiments of this application;

[0028] Figure 4C Z-data curves of a normalized single-channel image card and a grayscale image card are provided for embodiments of this application;

[0029] Figure 5A An X-ray data curve of a single-channel image card and a grayscale image card after superimposed compensation is provided in an embodiment of this application;

[0030] Figure 5B A Y-data curve of a single-channel image card and a grayscale image card after superimposed compensation is provided for an embodiment of this application;

[0031] Figure 5C Z-data curves of a single-channel image card and a grayscale image card after superimposed compensation, provided in an embodiment of this application;

[0032] Figure 6 A fitting curve diagram of RGB data and brightness contribution value provided in an embodiment of this application;

[0033] Figure 7 This is a schematic diagram of a grayscale transition effect provided in an embodiment of this application;

[0034] Figure 8 This is a schematic diagram illustrating another grayscale transition effect provided in an embodiment of this application;

[0035] Figure 9 This is a schematic diagram of the structure of a color calibration device provided in an embodiment of this application;

[0036] Figure 10 A connection diagram of a color calibration device, a display device, and a color analyzer provided in an embodiment of this application;

[0037] Figure 11 This application provides a schematic diagram of the structure of an electronic device. Detailed Implementation

[0038] With the advancement of technology, people have increasingly higher requirements for visual experience, and the color performance of various display devices has become an increasingly important factor in judging the quality of display devices.

[0039] Display devices typically emit light and display colors by controlling light-emitting units. Each light-emitting unit usually contains light-emitting points of three primary colors: R (Red), G (Green), and B (Blue). By adjusting the brightness and color intensity of each light-emitting point, the various light-emitting units in the display device can synthesize various colors. The display device can control each light-emitting unit to produce light of the corresponding color based on the values ​​of the three RGB channels in the input data. Specifically, when the values ​​of the three RGB channels are equal, grayscale light is produced, and the brightness increases as the RGB values ​​increase. Specifically, when all RGB values ​​are 0, the light-emitting units of various colors in the display device can theoretically not output light, presenting pure black; when all RGB values ​​are at their maximum values ​​(e.g., 255 in 8-bit color depth), the light-emitting units of the display device can theoretically output the brightest light, theoretically presenting pure white; when the RGB values ​​are between 0 and their maximum values, the light-emitting units of the display device can synthesize grayscale light of different brightness levels.

[0040] Due to differences in hardware design and manufacturing processes, different display devices typically exhibit varying color performance. Furthermore, with prolonged use, display devices may experience hardware malfunctions or aging, leading to a decline in color performance. In other words, different display devices, or display devices from different stages of development, may exhibit inaccurate color display, meaning there is a discrepancy between the colors displayed and the colors in the input signal.

[0041] In some implementations, color calibration can be performed on the display device to ensure that its color performance meets certain standards. This can be achieved by using a 3D LUT (3D Look-Up Table) to record the mapping relationship between color input and output values. By adjusting the mapping relationship in the 3D LUT table, potential deviations in color display can be corrected, ensuring accurate color display. However, after color calibration using existing methods, poor grayscale transitions can occur. For example, some grayscale values ​​may appear bluish-green, while others may appear pinkish, resulting in alternating red and green areas in the grayscale transition image, negatively impacting the user's visual experience.

[0042] Based on this, this solution proposes a color accuracy correction method for display devices. By fine-tuning the values ​​of each color channel in the target color output value within a certain fluctuation range, multiple sets of candidate color output values ​​are obtained. Then, the color deviation values ​​corresponding to these multiple sets of candidate color output values ​​are acquired, and the color deviation value (Deltauv, or duv for short) closest to 0 and greater than 0 is selected. The candidate color output value corresponding to this color deviation value is then used to replace the target color output value. In this way, fine-tuning the target color output value has almost no impact on the color accuracy of the image. Furthermore, after obtaining multiple candidate color output values, the color output value with the optimal grayscale performance can be determined based on the color deviation value. Then, replacing the original color output values ​​of the 3D LUT table with the optimal color output value for each grayscale level avoids red-green intermingling in the grayscale, resulting in a more uniform grayscale transition and improving the user's viewing experience.

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0044] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0045] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0046] In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0047] Figure 1 This is a schematic flowchart illustrating a color calibration method according to one embodiment of this application. The color calibration method can be executed by a color calibration device for color calibration of a display device. Specifically, it may include the following steps:

[0048] S102, obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to the preset fluctuation range to obtain multiple sets of candidate color output values.

[0049] In implementation, the target color output value can be obtained directly from an existing 3D LUT table, or it can be calculated based on the target color input value using a preliminary color accuracy correction method. For details on the preliminary correction process for the target color input value, please refer to [link to relevant documentation]. Figure 2 .

[0050] The target color is represented using a first color space. The target color input value can be any color input value corresponding to a single-channel chart or grayscale chart within the first color space. For example, the first color space can be the RGB color space, and correspondingly, the target color input value and the target color output value can be RGB values.

[0051] Furthermore, the target color input value can be selected according to the first sampling difference (or step size). Taking an 8-bit color depth as an example, the value range of each color channel is [0, 255]. When selecting the target color depth value with a step size of 32, it means that for each color channel in RGB, the value can start from 0 and increase by 32 each time until the maximum value of 255 is reached.

[0052] In implementation, the target color input value and the target color output value may include multiple color channels. Accordingly, the target color output value is adjusted according to a preset fluctuation range to obtain multiple sets of candidate color output values. Specifically, this may include the following processing: obtaining the values ​​of each color channel in the target color output value, adjusting the values ​​of each color channel separately according to the preset fluctuation range to obtain multiple candidate values; and combining the values ​​of the multiple color channels based on the multiple candidate values ​​of each color channel to obtain multiple sets of candidate color output values.

[0053] For example, the target color input value (16,16,16) corresponds to a target color output value of (14,13,12), including three color channels: R, G, and B. The R color channel value is 14, the G color channel value is 13, and the B color channel value is 12. When the preset fluctuation range is 1, the values ​​of the three color channels are ±1 respectively, resulting in candidate values ​​of 13, 14, and 15 for the R color channel; 12, 13, and 14 for the G color channel; and 11, 12, and 13 for the B color channel. Based on the candidate values ​​of each color channel, the values ​​of the three color channels are combined to obtain 3*3*3 possible combinations. See Table 8 for a total of 27 candidate color output values.

[0054] Figure 2 A flowchart illustrating a color calibration method provided in another embodiment of this application is shown, which may specifically include the following steps:

[0055] S202, select the input values ​​of single-channel color and grayscale color according to the first sampling difference to obtain several test charts.

[0056] In one embodiment, the target color input value can be the input value of each single-channel color and the input value of each grayscale color. The single-channel colors can be referred to as single-channel charts, and the grayscale colors can be referred to as grayscale charts.

[0057] For example, see Table 1, taking a first sampling difference of 32 as an example. Within the entire color range, that is, from 0 to 255, sampling is performed based on the first sampling difference, resulting in a total of 36 test charts, including 9 red single-channel charts, 9 green single-channel charts, 9 blue single-channel charts, and 9 grayscale charts.

[0058] It is worth mentioning that the single-channel chart described in this application refers to a chart in which only one channel has a value greater than 0, while the values ​​of other channels are all 0.

[0059] Table 1: Target Color Input Values ​​for Each Test Chart

[0060]

[0061] S204, obtain the color coordinates of each test pattern card when it is displayed on the display device, and calculate the target brightness value required for the test pattern card to reach the target color temperature.

[0062] In practice, the color coordinates are represented by two parameters, x and y, which correspond to the horizontal and vertical axes of the chromaticity diagram, respectively. Given the XYZ values ​​of each test chart, the corresponding color coordinates (x, y) can be calculated using the following formulas (1) and (2):

[0063]

[0064] Wherein, RX, GX, and BX represent the X values ​​corresponding to RGB single-channel graphics cards, RY, GY, and BY represent the Y values ​​corresponding to RGB single-channel graphics cards, and RZ, GZ, and BZ represent the Z values ​​corresponding to RGB single-channel graphics cards.

[0065] In one embodiment, each test chart can be displayed on a display device, and the XYZ data corresponding to each test chart can be measured using a CA410 color analyzer. For example, the measured XYZ data for the test charts shown in Table 1 can be found in Table 2. Correspondingly, the fitting curves of the RGB data and X, Y, and Z data corresponding to each single-channel chart and grayscale chart can be found in Table 2. Figures 3A to 3C .

[0066] Table 2: XYZ data measurement values ​​for each test chart

[0067]

[0068] In one embodiment, color accuracy correction can be performed according to a target color temperature. The target color temperature can be set according to business needs, and this application does not limit its value. For example, for televisions, the target color temperature can be set according to the common television standard of 9300K or 6500K.

[0069] The following explanation uses a target color temperature of 9300K, corresponding to target color coordinates (0.285, 0.293), as an example. It can be understood that the closer the color coordinates (x, y) of any single-channel or grayscale chart are to the target color coordinates, the closer the sum of the Y values ​​(RY+GY+BY) of the corresponding RGB single-channel charts will be to the target luminance value required to achieve the target color temperature. Since the luminance value corresponding to each test chart can be calculated based on the measured XYZ values, after determining the test chart that is closest to the target color coordinates (0.285, 0.293), luminance interpolation can be used to calculate the luminance value corresponding to the target color coordinates (0.285, 0.293), i.e., the luminance value required to achieve the target color temperature of 9300K.

[0070] In one embodiment, the proximity of the test chart's color coordinates (x, y) to the target color coordinates (0.285, 0.293) can be determined by calculating the differences Δx = x - 0.285 and Δy = y - 0.293 on the horizontal and vertical axes, respectively. If Δx and / or Δy are less than a preset difference, such as 0.5%, it can be determined that the color coordinates of that chart are relatively close to the target color coordinates. The target brightness value is then obtained by adding the Y values ​​corresponding to the three single-channel charts of that chart.

[0071] In an embodiment, the color coordinates of the test chart can be determined to be close to the color coordinates of the target color temperature when either Δx or Δy is less than a preset difference; alternatively, the color coordinates of the test chart can be determined to be close to the color coordinates of the target color temperature only when both Δx and Δy are less than preset values. Of course, other methods can be used to determine whether the color coordinates of each chart are close to the target color coordinates, and this application does not limit this.

[0072] S206, normalize the XYZ data of each test chart based on the target brightness value.

[0073] In practice, after calculating the luminance value required to achieve the target color temperature, this luminance value can be used as a baseline and scaled to 1. Then, the XYZ data of each test chart can be scaled using the same scaling ratio. For example, the results of normalizing the measured XYZ data shown in Table 2 can be found in Table 3. Correspondingly, the fitting curves of the RGB data corresponding to each single-channel chart and grayscale chart with the normalized X, Y, and Z data can be found in Table 3. Figures 4A to 4C .

[0074] Table 3: Normalized XYZ data measurements for each test chart

[0075]

[0076] S208 performs black field correction and overlay compensation on the XYZ data corresponding to each normalized test chart.

[0077] In one embodiment, when the display device displays a pure black test chart, theoretically no light is emitted, and the measured XYZ data values ​​are all 0. However, due to factors such as interference in the measurement environment, the actual XYZ data measured on a pure black chart may not be 0. To ensure the accuracy of the measurement and calculation results, black level correction can be performed on the normalized XYZ data corresponding to each test chart. This involves subtracting the XYZ data corresponding to a black screen (i.e., all RGB channel values ​​are 0) from the XYZ data corresponding to each test chart.

[0078] After black level correction, the XYZ data of each test chart can be superimposed for compensation. Therefore, the XYZ data of the grayscale chart will be equal to the sum of the corresponding R, G, and B single channels. This is understandable since grayscale is obtained by superimposing the RGB three-channel values ​​with the same pixel value. Therefore, each single-channel chart and grayscale chart can satisfy the following formulas (3) to (5):

[0079]

[0080] Where, compensate_R[j].X is the X value of the j-th red channel after superposition compensation, and RGB[j].X is the X value of the j-th gray level acquired. In this embodiment, the step size used for each test chart is 32, so there are a total of 9 numbers in the range of [0,255]. j starts from 0, so R[8].X is the X value of the 9th red single-channel chart (255,0,0) acquired, G[8].X is the X value of the 9th green single-channel chart (0,255,0) acquired, and B[8].X is the X value of the 9th blue single-channel chart (0,0,255) acquired.

[0081] Similarly, compensate_R[j].Y is the Y value of the j-th red channel after superposition compensation, and RGB[j].Y is the Y value of the j-th gray level acquired. R[8].Y is the Y value of the 9th red single-channel image card (255,0,0) acquired, G[8].Y is the Y value of the 9th green single-channel image card (0,255,0) acquired, and B[8].Y is the Y value of the 9th blue single-channel image card (0,0,255) acquired.

[0082] conpensate_R[j].Z is the Z value of the j-th red channel after superposition compensation, RGB[j].Z is the Z value of the j-th grayscale acquired. R[8].Z is the Z value of the 9th red single-channel image card (255,0,0) acquired, G[8].Z is the Z value of the 9th green single-channel image card (0,255,0) acquired, and B[8].Z is the Z value of the 9th blue single-channel image card (0,0,255) acquired.

[0083] It is worth mentioning that j represents the sequence number, used for counting. Therefore, if j starts from 1, R[8].X is the X value of the 9th red single-channel chart (255,0,0) collected. Other XYZ values ​​are similar, and will not be described in detail in this application.

[0084] In one embodiment, the results of the superimposed compensation calculation of the XYZ values ​​corresponding to the single-channel graphics card based on the above formulas (3) to (5) can be found in Table 4. Correspondingly, the fitting curves of the RGB data corresponding to each single-channel graphics card and the grayscale graphics card with the superimposed compensated X, Y, and Z data can be found in the following tables: Figures 5A to 5C .

[0085] Table 4: XYZ data measurements after superposition compensation for each test chart

[0086]

[0087] S210, establish the mapping relationship between RGB data and the output brightness value of each channel, RGB data and XYZ data, and XYZ data and the output brightness value of each channel.

[0088] For ease of description, the mapping relationship between RGB data and XYZ data can be called the first mapping relationship; the mapping relationship between XYZ data and the brightness contribution of each channel can be called the second mapping relationship; and the mapping relationship between the brightness contribution of each channel and RGB data can be called the third mapping relationship.

[0089] In this embodiment, there are certain mapping relationships between RGB data and the output brightness values ​​of each channel, between RGB data and XYZ data, and between XYZ data and the output brightness values. Therefore, by establishing these mapping relationships, the corresponding target color output value can be calculated based on the target color input value. Thus, when the display device receives the target color input value, in order to display the corresponding color more accurately, the light-emitting unit can be controlled according to the target color output value.

[0090] Specifically, the process of establishing and solving the above mapping relationship can include the following steps.

[0091] In one embodiment, there is a certain mapping relationship between the RGB digital driving values ​​Di(i=r,g,b) of the display device and the output brightness Yi(i=r,g,b), which can be expressed by a functional relationship. Therefore, this functional relationship can be established first. For example, a Lagrange interpolation algorithm can be used to select a cubic function to express the mapping relationship between Di(i=r,g,b) and Yi(i=r,g,b). Based on the RGB digital driving values ​​Di(i=r,g,b) shown in Table 1 and the output brightness Yi(i=r,g,b) calculated from the measured values ​​of XYZ data of each test card, the parameters of this cubic function can be automatically obtained. It can be understood that once the functional relationship reflecting the mapping relationship between Di(i=r,g,b) and Yi(i=r,g,b) is obtained, the output brightness value can be calculated by inputting any RGB card data.

[0092] In one embodiment, the RGB color space and the CIEXYZ chromaticity space can be spatially transformed based on a certain algorithm, such as a linear transformation. Therefore, a basic algorithm can be established to transform the RGB digital driving values ​​and theoretical XYZ data spatially to represent their mapping relationship.

[0093] In one embodiment, a mapping relationship between the XYZ data corresponding to each test chart and the RGB channel contribution brightness (or output brightness) can also be established based on a 3×3 matrix, see equation (6).

[0094]

[0095] Where X(255,0,0), Y(255,0,0), and Z(255,0,0) represent the XYZ values ​​of the red single-channel chart (255,0,0). X(0,255,0), Y(0,255,0), and Z(0,255,0) represent the XYZ values ​​of the green single-channel chart (0,255,0). X(0,0,255), Y(0,0,255), and Z(0,0,255) represent the XYZ values ​​of the blue single-channel chart (0,0,255).

[0096] Yr(255), Yg(0), Yb(0) represent the luminance values ​​contributed by the R, G, and B channels in the red single-channel chart (255,0,0). Yr(0), Yg(255), Yb(0) represent the luminance values ​​contributed by the R, G, and B channels in the green single-channel chart (0,255,0). Yr(0), Yg(0), Yb(255) represent the luminance values ​​contributed by the R, G, and B channels in the blue single-channel chart (0,0,255). Yr(0), Yg(0), Yb(0) represent the luminance values ​​contributed by the R, G, and B channels in the black chart (0,0,0), which are approximately equal to 0.

[0097] In this embodiment, the three single-channel graphics cards with the largest values ​​in the red, green, and blue channels were selected. Since the measured values ​​of the nine XYZ data on the left side of the equation are known, the nine contribution brightness values ​​corresponding to each channel on the right side of the equation can also be calculated based on the corresponding Y values. Thus, by substituting the above data into equation (6), the 3×3 transformation matrix can be calculated, that is, the values ​​of a11, a12, a13, a21, a22, a23, a31, a32, and a33 can be calculated.

[0098] In one embodiment, after step S202, black level correction and overlay compensation can be directly performed on the XYZ data acquired using the CA410 color analyzer, i.e., the actual measured values. Correspondingly, the black level correction and overlay compensation can be performed on the data. Figure 2 Steps S202-S208 are replaced by the following processing: Multiple grayscale colors and multiple single-channel colors are selected as color input values ​​according to the first sampling difference, and the actual measured values ​​of each color input value when displayed on the display device are obtained; wherein, the actual measured values ​​include output brightness values ​​and are represented using a second color space; black level correction and superposition compensation are performed on each actual measured value to obtain the superimposed compensated theoretical measured value. Furthermore, based on each theoretical measured value, a second mapping relationship between the theoretical measured value and the output brightness can be calculated.

[0099] In another embodiment, to reduce measurement and calculation errors, the measured XYZ data can be normalized based on the target brightness value. Accordingly, steps S204-S206 may include: calculating the color coordinates corresponding to each color input value based on the actual measured values, and determining the target brightness value required to reach the target color coordinates based on multiple color coordinates; scaling the actual measured values ​​corresponding to each color input value based on the target brightness value to obtain scaled actual measured values. Furthermore, step S208 may include: performing black level correction and superposition compensation on each scaled actual measured value to obtain a superimposed compensated theoretical measured value.

[0100] In practice, the aforementioned 3×3 conversion matrix represents the second mapping relationship between the theoretical measured value and the output brightness.

[0101] Furthermore, using the inverse of this 3×3 transformation matrix, the corresponding output luminance Yi (i = r, g, b) can be calculated based on the measured XYZ data of each single-channel graphics card. The luminance contribution values ​​for each channel can be found in Table 5. Correspondingly, the fitting curves of the RGB data and luminance contribution values ​​for each single-channel graphics card can be found in [Table 5]. Figure 6 .

[0102] Table 5: Brightness Contribution Value of Each Channel

[0103] index Red Channel Contribution Value Green Channel Contribution Value Blue Channel Contribution Value 0 0.000000 0.000000 0.000000 32 0.002673 0.008077 0.001837 64 0.011717 0.036275 0.008135 96 0.027857 0.087893 0.019580 128 0.052074 0.165967 0.036151 160 0.085014 0.274214 0.059200 192 0.126397 0.410440 0.089224 224 0.176293 0.575428 0.126265 255 0.229231 0.750576 0.169178

[0104] Since the XYZ data of a grayscale image card is theoretically equal to the sum of the XYZ data of the corresponding R, G, and B single channels, the grayscale image card satisfies equation (7).

[0105]

[0106] Where X(255,255,255) represents the XYZ values ​​of the white pattern (255,255,255). Yr(255), Yg(255), and Yb(255) represent the brightness values ​​contributed by the R, G, and B channels in the white pattern (255,255,255).

[0107] In one embodiment, the output brightness corresponding to each grayscale color can be calculated based on the second mapping relationship; then, based on the color input values ​​of multiple grayscale colors and their corresponding output brightness, a third mapping relationship between the color input values ​​and the output brightness can be calculated.

[0108] In other words, after measuring the XYZ data of any grayscale chart Di (i = r, g, b), the output brightness Yi (i = r, g, b) corresponding to that grayscale chart can be calculated based on formula (7), which includes the contribution brightness of the R, G, and B channels respectively. See Figure 6 Based on the known luminance contributions of the R, G, and B channels of a grayscale image card, luminance contribution curves for each of the three channels can be plotted. Therefore, based on the RGB digital driving values ​​Di(i = r, g, b) and the corresponding output luminance Yi(i = r, g, b) of the known data points on the curves, the function expressions corresponding to the luminance contribution curves of the R, G, and B channels can be automatically calculated. The function expressions corresponding to the three luminance contribution curves reflect the third mapping relationship between the RGB digital driving values ​​Di(i = r, g, b) and Yi(i = r, g, b).

[0109] S212, based on the multiple mapping relationships established in step S210, calculate the target color output value corresponding to the target color input value.

[0110] In practice, when any RGB image card is input, that is, when the target color input value is arbitrary, the theoretical measurement value (i.e., theoretical XYZ data) corresponding to the target color input value can be calculated based on the first mapping relationship between RGB data and XYZ data, that is, through color gamut space conversion.

[0111] In practice, although different color spaces differ in their expression methods and physical meanings, they are all used to describe colors, and each color has a corresponding representation in different color gamut spaces. Therefore, through color gamut space conversion, colors in the RGB color space can be converted to the XYZ color space. Based on this, the mapping relationship between RGB data and XYZ data can be calculated using the known RGB data (see Table 1) and XYZ data (see Table 4) of various test charts. Of course, the mapping relationship between RGB data and XYZ data can also be determined based on known mathematical conversion formulas and color matching functions; this application does not impose any restrictions on this approach.

[0112] Then, based on the second mapping relationship between the XYZ data and the contribution brightness of each channel, namely the 3×3 transformation matrix mentioned above, the target contribution brightness (i.e., Target_Yi (i=r,g,b)) corresponding to the theoretical measurement value (i.e., theoretical XYZ data) can be calculated.

[0113] Then, a third mapping relationship can be established between the brightness contribution of each channel and the RGB data, i.e. Figure 6 The brightness contribution curve shown is interpolated to obtain the target color output value (i.e., target RGB data, which can be denoted as Target_R, Target_G, Target_B) corresponding to the target contribution brightness (i.e., Target_Yi (i=r,g,b)).

[0114] In one embodiment, to determine whether color calibration was successful—that is, whether the target color output value calculated using the above mapping relationship meets the standard—a color analyzer can be used to measure the actual XYZ data when the display device controls the light-emitting unit using the target color output value. Then, the success of color calibration is determined based on the color accuracy value (DeltaE, abbreviated as ΔE) between the actual XYZ data and the theoretical XYZ data. If the color accuracy value is less than a preset color accuracy threshold, it indicates that the display device has successfully calibrated the color accuracy for the graphics card. Conversely, if the calculated color accuracy value exceeds the preset color accuracy threshold, it indicates that the color calibration was unsuccessful.

[0115] It is understandable that the preset color accuracy threshold can be set according to different types and models of display devices. For example, the preset color accuracy threshold can be between 1.5 and 2; the more stringent the color accuracy standard, the smaller the value can be.

[0116] In one embodiment, after Figure 2 The method shown involves calculating the target color output values ​​corresponding to each grayscale chart for a certain display device. Although the color accuracy of each grayscale chart meets the preset color accuracy threshold, some grayscale levels exhibit a bluish-green tint, while others show a pinkish tint. (See also...) Figure 7 When based on adoption Figure 2After the color accuracy correction method shown corrects the RGB driving values ​​in the 3D LUT, when a grayscale transition image is displayed on a display device, some grayscale levels appear bluish-green, while others appear pinkish, resulting in a noticeable red-green alternation. This indicates poor grayscale transition, negatively impacting the user's visual experience.

[0117] In this case, the target color output value can also be adjusted. Figure 1 In step S102, fine-tuning is performed to obtain multiple possible candidate color output values.

[0118] In one implementation, the higher the grayscale level, the more precise the display device's control over brightness, resulting in a more detailed image. Based on this, another embodiment of the color accuracy correction method provided in this application may include: increasing the selected target color input value according to the second sampling difference.

[0119] In practice, the second sampling difference is smaller than the first sampling difference. This allows for sampling and color accuracy correction of the target color output values ​​corresponding to each grayscale level at smaller intervals. Consequently, it enables more accurate capture of the display's color performance in various brightness areas, resulting in smoother brightness transitions between grayscale levels and thus improving the overall accuracy of color reproduction and the level of image detail.

[0120] In one embodiment, the display device may find it difficult to control the color brightness of certain grayscale ranges, while it may find it easier to control the brightness of other grayscale ranges. Accordingly, another embodiment of the color accuracy correction method provided in this application may include the following steps: selecting a target color input value within a preset grayscale range according to a second sampling difference.

[0121] It is worth mentioning that the preset grayscale range can be set according to the actual application scenario and business needs, and this application does not restrict its value.

[0122] In one embodiment, when the grayscale level decreases to a certain extent, the display device may be unable to accurately control the corresponding color brightness, thus making color cast more likely. In contrast, brighter grayscale levels have higher color brightness across the RGB channels, making it easier for the display device to accurately control their brightness, resulting in less color cast. In this case, sampling can be increased for the mid-to-low grayscale levels, i.e., a second sampling difference smaller than the first sampling difference can be used to increase the selection of grayscale charts within the mid-to-low grayscale range, thereby performing color accuracy correction on the grayscale charts within the mid-to-low grayscale range.

[0123] For example, the low to medium grayscale can be a range from 0 to 128, that is, the preset grayscale range is 0-128. The first sampling difference is 32, the second sampling difference is 16, and the second sampling difference is half of the first sampling difference. As shown in Table 6, when sampling is performed based on the second sampling difference of 16 within the low grayscale range, i.e. from grayscale 0 to grayscale 128, a total of 9 grayscale charts can be obtained, including grayscale 0, grayscale 16, grayscale 32, grayscale 48, grayscale 64, grayscale 80, grayscale 96, grayscale 112 and grayscale 128. The corresponding target color input values ​​are (0,0,0), (16,16,16), (32,32,32), (48,48,48), (64,64,64), (80,80,80), (96,96,96), (112,112,112) and (128,128,128). Comparing Tables 1 and 6, it can be seen that sampling based on the second sampling difference of 16, compared to sampling based on the first sampling difference of 32, adds 4 grayscale images to the low and medium grayscale range, including grayscale 16, grayscale 48, grayscale 80 and grayscale 112.

[0124] Table 6: Target color input values ​​within the low to medium grayscale range of 0-128

[0125]

[0126] In this way, by only increasing the number of gray levels within the preset grayscale range, on the one hand, the preset grayscale range, which is more prone to poor grayscale transitions, can obtain more detailed color accuracy correction, thereby making the brightness transition between adjacent grayscale levels smoother; on the other hand, compared to increasing the number of gray levels across the entire range, that is, increasing the number of sampled grayscale levels across the entire grayscale range, the computational load of color accuracy correction can be significantly reduced, reducing the computational burden on the color accuracy correction device and improving the speed of color accuracy correction.

[0127] In one implementation, the target color output value corresponding to the increased target color input value can be directly adopted. Figure 2 The mapping relationship obtained in the color accuracy correction method shown is used for calculation. Accordingly, the color accuracy correction method provided in this embodiment may further include: calculating the theoretical measurement value corresponding to the target color input value based on the first mapping relationship; wherein the theoretical measurement value is represented using a second color space; calculating the target contribution brightness corresponding to the theoretical measurement value based on the second mapping relationship; and calculating the target color output value corresponding to the target contribution brightness based on the third mapping relationship.

[0128] In practice, the second color space can be the XYZ color space, and correspondingly, the theoretical measurement value can be the theoretical XYZ data. For the calculation method of the target color output value, please refer to [link / reference needed]. Figure 2The process shown is not detailed here. Accordingly, the target color output values ​​calculated from the target color input values ​​in Table 6 can be found in Table 7.

[0129] Table 7: Target color output values ​​corresponding to the target color input values ​​shown in Table 6

[0130]

[0131] Furthermore, taking the target color input value (16,16,16) as an example, after calculation using a 3x3 transformation matrix, as follows: Figure 7 As shown, the target color output value (14,13,12) corresponding to the target color input value (16,16,16) is obtained. Then, fine-tuning the target color output value (14,13,12) yields the following result: Figure 8 The output values ​​for the candidate colors are shown.

[0132] Table 8: The candidate color output values ​​obtained after fine-tuning the target color output value (14, 13, 12).

[0133]

[0134] S104, obtain the color deviation value of each candidate color output value when displayed on the display device, and determine the optimal value from multiple color deviation values.

[0135] In implementation, after fine-tuning the target color output value to obtain multiple candidate color output values, these values ​​can be evaluated based on the color deviation value (DUV). The DUV, measured by a color analyzer, reflects the purity and accuracy of the colors displayed by the display device. Specifically, the color calibration device sends multiple candidate color output values ​​to the display device, enabling the device to control the light-emitting units to display the corresponding color based on each value. While the display device displays each candidate color output value, the corresponding DUV can be measured using a color analyzer. For example... Figure 8 The correspondence between the output values ​​of the candidate colors and the DUV values ​​can be found in Table 9.

[0136] Table 9: Correspondence between candidate color output values ​​and DUUV values

[0137]

[0138] In one embodiment, the optimal value can be selected as the one where the difference between the duv value and 0 is the smallest. It can be understood that the closer the duv value is to 0, that is, the smaller the absolute value of the color deviation duv, the better the accuracy of color display. This means that the color is purer, without excessive noise or color cast.

[0139] In another embodiment, the smallest non-negative value from multiple duv values ​​can be selected as the optimal value. When the duv value is close to 0 but greater than 0, the displayed color is yellowish-green. When the smallest non-negative value is selected, the color accuracy correction is closer to the color temperature of natural light, which generally provides a more comfortable visual experience.

[0140] S106, update the target color output value using the candidate color output value corresponding to the optimal value.

[0141] In implementation, the optimal value can be determined according to preset rules. For example, the optimal value can be the DUUV value that differs least from 0, or it can be the smallest non-negative value among multiple DUUV values. Once the optimal value is determined, the candidate color output value corresponding to the optimal value can be set as the best output value corresponding to the target color input value, and this best output value is used to update the target color output value. For example, in the corresponding position of the 3D LUT table, the target color output value corresponding to the target color input value is replaced with the candidate color output value corresponding to the optimal value.

[0142] See Figure 8 This application adopts Figure 1 The illustrated embodiment allows for fine-tuning with almost no impact on color accuracy, and by replacing the original RGB values ​​with the optimal RGB values ​​for each grayscale level, it avoids the appearance of alternating red and green hues in the grayscale. Compared to Figure 7 The grayscale transition effect shown is Figure 8 The grayscale transitions are more uniform, improving the user's viewing experience.

[0143] Based on the same technical concept, embodiments of this application also provide a color calibration device. In one embodiment, see... Figure 9 The color calibration device can be a separate computing device, connected to both the color analyzer and the display device. Alternatively, the color calibration device can be integrated into either the color analyzer or the display device; this application does not limit this. See also Figure 10 The color calibration device may include:

[0144] The fine-tuning module is used to obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to a preset fluctuation range to obtain multiple sets of candidate color output values; wherein, the target color is represented using a first color space, and the target color input value is selected according to a first sampling difference;

[0145] The selection module is used to obtain the color deviation value when each of the candidate color output values ​​is displayed on the display device, and to determine the optimal value from the multiple color deviation values.

[0146] The update module is used to update the target color output value using the candidate color output value corresponding to the optimal value.

[0147] Optionally, the color calibration device further includes:

[0148] The sampling module is used to add the target color input value according to the second sampling difference; wherein the second sampling difference is less than the first sampling difference.

[0149] Optionally, the color calibration device further includes:

[0150] Within a preset grayscale range, the target color input value is increased by a second sampling difference; wherein the second sampling difference is less than the first sampling difference.

[0151] Optionally, the color calibration device further includes a mapping module for:

[0152] Based on the first mapping relationship, the theoretical measurement value corresponding to the target color input value is calculated; wherein the theoretical measurement value is represented using the second color space;

[0153] Based on the second mapping relationship, the target contribution brightness corresponding to the theoretical measurement value is calculated;

[0154] Based on the third mapping relationship, the target color output value corresponding to the target contribution brightness is calculated.

[0155] Optionally, the first mapping relationship is a color gamut space conversion relationship between the color input value in the first color space and the theoretical measurement value in the second color space.

[0156] Optionally, the mapping module is also specifically used for:

[0157] Multiple grayscale colors and multiple single-channel colors are selected according to the first sampling difference, and the actual measured value of each of the color input values ​​is obtained when it is displayed on the display device; wherein, the actual measured value includes the output brightness value and is represented using the second color space;

[0158] Black field correction and superposition compensation are performed on each of the actual measured values ​​to obtain the theoretical measured value after superposition compensation.

[0159] Based on each of the theoretical measurements, the second mapping relationship between the theoretical measurements and the output brightness is calculated.

[0160] Optionally, the mapping module is also specifically used for:

[0161] The color coordinates corresponding to each color input value are calculated based on the actual measured values ​​corresponding to each color input value, and the target brightness value required to achieve the target color coordinates is determined based on multiple color coordinates.

[0162] Based on the target brightness value, the actual measured values ​​corresponding to each of the color input values ​​are scaled to obtain scaled actual measured values.

[0163] Black field correction and superposition compensation are performed on each of the scaled actual measurement values ​​to obtain the superimposed and compensated theoretical measurement value.

[0164] Optionally, the mapping module is also specifically used for:

[0165] Based on the second mapping relationship, calculate the output brightness corresponding to each grayscale color;

[0166] Based on the color input values ​​of the multiple grayscale colors and the corresponding output brightness, the third mapping relationship between the color input values ​​and the output brightness is calculated.

[0167] Optionally, the fine-tuning module is specifically used for:

[0168] Obtain the values ​​of each color channel in the target color output value, and adjust the values ​​of each color channel according to a preset fluctuation range to obtain multiple candidate values;

[0169] Based on multiple candidate values ​​for each of the color channels, the values ​​of the multiple color channels are combined to obtain multiple sets of candidate color output values.

[0170] It should be noted that the color calibration device provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the color calibration device and color calibration method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0171] Based on the same technical concept, this application also provides an electronic device, see [link to relevant documentation]. Figure 11 The system includes a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed as described in any of the above embodiments.

[0172] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This color calibration software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including storing several instructions to cause an electronic device to execute the methods described in various embodiments or some parts of the embodiments.

[0173] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A color accuracy calibration method for a display device, characterized in that, The color accuracy correction method includes: Obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to a preset fluctuation range to obtain multiple sets of candidate color output values; wherein, the target color is represented using a first color space, and the target color input value is selected according to a first sampling difference; Obtain the color deviation value of each of the candidate color output values ​​when displayed on the display device, and determine the optimal value from the multiple color deviation values; The target color output value is updated using the candidate color output value corresponding to the optimal value.

2. The color accuracy correction method as described in claim 1, characterized in that, The color accuracy correction method also includes: The target color input value is selected according to the second sampling difference; wherein the second sampling difference is less than the first sampling difference.

3. The color accuracy correction method as described in claim 2, characterized in that, The color accuracy correction method also includes: Within a preset grayscale range, the target color input value is selected according to the second sampling difference.

4. The color accuracy correction method according to any one of claims 1-3, characterized in that, The color accuracy correction method also includes: Based on the first mapping relationship, the theoretical measurement value corresponding to the target color input value is calculated; wherein, the theoretical measurement value is represented using the second color space; Based on the second mapping relationship, the target contribution brightness corresponding to the theoretical measurement value is calculated; Based on the third mapping relationship, the target color output value corresponding to the target contribution brightness is calculated.

5. The color accuracy correction method as described in claim 4, characterized in that, The first mapping relationship is the color gamut space conversion relationship between the color input value in the first color space and the theoretical measurement value in the second color space.

6. The color accuracy correction method as described in claim 4, characterized in that, Before obtaining the target color output value corresponding to the target color input value, the color accuracy correction method further includes: Multiple grayscale colors and multiple single-channel colors are selected according to the first sampling difference, and the actual measured values ​​of each of the color input values ​​are obtained when they are displayed on the display device; wherein, the actual measured values ​​include output brightness values ​​and are represented using the second color space; Black field correction and superposition compensation are performed on each of the actual measured values ​​to obtain the theoretical measured value after superposition compensation. Based on each of the theoretical measurements, the second mapping relationship between the theoretical measurements and the output brightness is calculated.

7. The color accuracy correction method as described in claim 6, characterized in that, The step of performing black field correction and superposition compensation on each of the actual measured values ​​to obtain the superimposed and compensated theoretical measured values ​​includes: The color coordinates corresponding to each color input value are calculated based on the actual measured values ​​corresponding to each color input value, and the target brightness value required to achieve the target color coordinates is determined based on multiple color coordinates. Based on the target brightness value, the actual measured values ​​corresponding to each of the color input values ​​are scaled to obtain scaled actual measured values. Black field correction and superposition compensation are performed on each of the scaled actual measurement values ​​to obtain the superimposed and compensated theoretical measurement value.

8. The color accuracy correction method as described in claim 4, characterized in that, Based on the second mapping relationship, calculate the output brightness corresponding to each grayscale color; Based on the color input values ​​of the multiple grayscale colors and the corresponding output brightness, the third mapping relationship between the color input values ​​and the output brightness is calculated.

9. The color accuracy correction method as described in claim 1, characterized in that, The optimal value is the color deviation value with the smallest absolute value among the multiple color deviation values.

10. The color accuracy correction method as described in claim 1, characterized in that, The target color output value is adjusted according to a preset fluctuation range to obtain multiple sets of candidate color output values, including: Obtain the values ​​of each color channel in the target color output value, and adjust the values ​​of each color channel according to a preset fluctuation range to obtain multiple candidate values; Based on multiple candidate values ​​for each of the color channels, the values ​​of the multiple color channels are combined to obtain multiple sets of candidate color output values.

11. A color calibration device, characterized in that, include: The fine-tuning module is used to obtain the target color output value corresponding to the target color input value, and adjust the target color output value according to a preset fluctuation range to obtain multiple sets of candidate color output values; wherein, the target color is represented using a first color space, and the target color input value is selected according to a first sampling difference; The selection module is used to obtain the color deviation value of each of the candidate color output values ​​when displayed on the display device, and to determine the optimal value from the multiple color deviation values. The update module is used to update the target color output value using the candidate color output value corresponding to the optimal value.

12. The color calibration device as described in claim 11, characterized in that, The color calibration device also includes: The sampling module is used to add the target color input value within a preset grayscale range according to a second sampling difference; wherein the second sampling difference is less than the first sampling difference.

13. The color calibration device as described in any one of claims 11-12, characterized in that, The color calibration device further includes a mapping module for: Based on the first mapping relationship, the theoretical measurement value corresponding to the target color input value is calculated; wherein, the theoretical measurement value is represented using the second color space; Based on the second mapping relationship, the target output brightness value corresponding to the theoretical measurement value is calculated; Based on the third mapping relationship, the target color output value corresponding to the target output brightness value is calculated.

14. An electronic device, characterized in that, include: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed as described in any one of claims 1-10.

15. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the color calibration method as described in any one of claims 1-10.

Images