Display screen brightness control method, device, equipment, storage medium and program product

Abstract

This application relates to a method, apparatus, device, storage medium, and program product for controlling the brightness of a display screen. The method includes: determining, based on the refresh rate of the display screen, a maximum brightness value, a gamma coefficient, and the color coordinates of each gamma binding point; determining the target brightness value and target tristimulus value corresponding to each gamma binding point; obtaining preset values ​​for each gamma binding point; searching for neighboring gamma binding points based on the preset values ​​of the gamma binding points to be corrected, and obtaining the measured tristimulus values ​​corresponding to the neighboring gamma binding points; determining an adjustment step based on the error between the measured tristimulus values ​​and the target tristimulus values; and re-searching for neighboring gamma binding points by adjusting the step until the error between the measured tristimulus values ​​corresponding to the searched gamma binding points and the target tristimulus values ​​meets a preset error function threshold, thus obtaining the corrected gamma binding point. This effectively improves the correction speed of gamma binding points and ensures that the brightness and color coordinates of the gamma binding points meet the requirements.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to a display screen brightness control method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] Gamma is a parameter used to characterize the brightness response characteristics of Active-Matrix Organic Light Emitting Diode (AMOLED) display devices. It evaluates the display effect of a module by assessing whether the relationship between display brightness and input level approximates an exponential curve. This curve is an important indicator of the chromaticity and brightness of AMOLED displays and also forms the basis for debugging the performance of other algorithms in AMOLED driver integrated circuits (ICs).

[0003] In traditional technology, the main method for gamma tuning is to use a trial-and-error approach. This involves adjusting the voltage setting by writing data values ​​into specific registers of the display driver chip to change the brightness of the R, G, and B sub-pixels respectively. The data values ​​are then changed in steps by the feedback from the color analyzer, so that the gamma and color coordinates gradually approach the specified values.

[0004] However, this method is complex and time-consuming, making it unsuitable for rapid calibration of gamma binding points on a large number of display modules. Summary of the Invention

[0005] Therefore, it is necessary to provide a display brightness control method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can quickly correct the gamma-tethered dots of the display module, addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides a method for controlling the brightness of a display screen, including:

[0007] Based on the refresh rate of the display screen, determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point;

[0008] Based on the maximum luminance value, the gamma coefficient, and the color coordinates of each gamma binding point, the target luminance value and target tristimulus value corresponding to each gamma binding point are determined respectively; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0009] Obtain the preset values ​​for each gamma binding point;

[0010] Select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0011] Based on the error between the measured tristimulus values ​​and the target tristimulus values, the adjustment step size for each color channel is determined.

[0012] By adjusting the step size of each color channel, the search continues to find neighboring gamma binding points until the error between the measured tristimulus value corresponding to the found gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently found gamma binding point is determined to be the corrected gamma binding point.

[0013] In one embodiment, determining the target luminance value and target tristimulus value corresponding to each gamma binding point based on the maximum luminance value, the gamma coefficient, and the chromatic coordinates of each gamma binding point includes:

[0014] Set the grayscale value corresponding to each gamma binding point, wherein the brightness corresponding to the maximum grayscale value is the maximum brightness value;

[0015] The target brightness value corresponding to each gamma binding point is determined based on the grayscale value corresponding to each gamma binding point, the maximum brightness, and the gamma coefficient.

[0016] Based on the color coordinates and target brightness values ​​corresponding to each gamma binding point, the target tristimulus values ​​corresponding to each gamma binding point are determined.

[0017] In one embodiment, obtaining the preset values ​​for each gamma binding point includes:

[0018] The R, G, and B channel values ​​corresponding to the largest and second largest gamma binding points were determined using a color analyzer.

[0019] Using the R-channel, G-channel, and B-channel values ​​corresponding to the largest and second largest gamma binding points as prior conditions, the R-channel, G-channel, and B-channel values ​​corresponding to the remaining gamma binding points are derived sequentially; wherein, the R-channel, G-channel, and B-channel values ​​corresponding to the gamma binding points constitute the preset values ​​of the gamma binding points.

[0020] In one embodiment, determining the adjustment step size for each color channel based on the error between the measured tristimulus value and the target tristimulus value includes:

[0021] If the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, the adjustment step of each color channel is set to a uniform adjustment step according to empirical parameters.

[0022] If the gamma binding point to be corrected is not the largest gamma binding point or the second largest gamma binding point, normalize the target tristimulus value and the measured tristimulus value respectively to obtain the first vector corresponding to the target tristimulus value and the second vector corresponding to the measured tristimulus value.

[0023] The similarity between the first vector and the second vector is determined by the cosine function;

[0024] The adjustment step size for each color channel is determined based on the similarity, the target tristimulus value, the measured tristimulus value, and the preset weight adjustment parameters.

[0025] In one embodiment, the step of re-searching for neighboring gamma binding points by adjusting the step size of each color channel includes:

[0026] If the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, decrease the value of the G channel by one adjustment step; if the measured red primary stimulus value is greater than the target red primary stimulus value, decrease the value of the R channel by one adjustment step; if the measured blue primary stimulus value is greater than the target blue primary stimulus value, decrease the value of the B channel by one adjustment step.

[0027] If the gamma binding point to be corrected is not the largest or second largest gamma binding point, then increase the values ​​of the R channel, G channel, and B channel by the corresponding adjustment step of the color channel.

[0028] In one embodiment, after determining the adjustment step size for each color channel based on the error between the measured tristimulus value and the target tristimulus value, the method further includes:

[0029] Determine whether the current number of searches for neighboring gamma binding points has reached the required number of iterations for the binding point interval where the gamma binding point to be corrected is located;

[0030] If the number of iterations is reached, the search stops.

[0031] Select the gamma binding point corresponding to the optimal search value from the already searched gamma binding points as the corrected gamma binding point.

[0032] In one embodiment, after determining that the currently searched gamma binding point is a corrected gamma binding point, the method further includes:

[0033] Determine whether the calibration of all gamma binding points has been completed;

[0034] Once all gamma binding points have been calibrated, the process ends.

[0035] If not all gamma binding points have been calibrated, the next uncalibrated gamma binding point is selected as the gamma binding point to be calibrated.

[0036] The gamma binding points to be corrected are corrected until all gamma binding points are corrected.

[0037] Secondly, this application also provides a display screen brightness control device, the device comprising:

[0038] The first determining module is used to determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen.

[0039] The second determining module is used to determine the target brightness value and target tristimulus value corresponding to each gamma binding point based on the maximum brightness value, the gamma coefficient, and the color coordinates of each gamma binding point; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0040] The acquisition module is used to obtain the preset values ​​of each gamma binding point;

[0041] The search module is used to select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0042] The step size determination module is used to determine the adjustment step size of each color channel based on the error between the measured tristimulus value and the target tristimulus value.

[0043] The search module is further configured to re-search for neighboring gamma binding points by adjusting the step size of each color channel until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently searched gamma binding point is determined to be the corrected gamma binding point.

[0044] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0045] Based on the refresh rate of the display screen, determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point;

[0046] Based on the maximum luminance value, the gamma coefficient, and the color coordinates of each gamma binding point, the target luminance value and target tristimulus value corresponding to each gamma binding point are determined respectively; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0047] Obtain the preset values ​​for each gamma binding point;

[0048] Select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0049] Based on the error between the measured tristimulus values ​​and the target tristimulus values, the adjustment step size for each color channel is determined.

[0050] By adjusting the step size of each color channel, the search continues to find neighboring gamma binding points until the error between the measured tristimulus value corresponding to the found gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently found gamma binding point is determined to be the corrected gamma binding point.

[0051] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0052] Based on the refresh rate of the display screen, determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point;

[0053] Based on the maximum luminance value, the gamma coefficient, and the color coordinates of each gamma binding point, the target luminance value and target tristimulus value corresponding to each gamma binding point are determined respectively; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0054] Obtain the preset values ​​for each gamma binding point;

[0055] Select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0056] Based on the error between the measured tristimulus values ​​and the target tristimulus values, the adjustment step size for each color channel is determined.

[0057] By adjusting the step size of each color channel, the search continues to find neighboring gamma binding points until the error between the measured tristimulus value corresponding to the found gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently found gamma binding point is determined to be the corrected gamma binding point.

[0058] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0059] Based on the refresh rate of the display screen, determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point;

[0060] Based on the maximum luminance value, the gamma coefficient, and the color coordinates of each gamma binding point, the target luminance value and target tristimulus value corresponding to each gamma binding point are determined respectively; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0061] Obtain the preset values ​​for each gamma binding point;

[0062] Select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0063] Based on the error between the measured tristimulus values ​​and the target tristimulus values, the adjustment step size for each color channel is determined.

[0064] By adjusting the step size of each color channel, the search continues to find neighboring gamma binding points until the error between the measured tristimulus value corresponding to the found gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently found gamma binding point is determined to be the corrected gamma binding point.

[0065] The aforementioned display screen brightness control method, device, computer equipment, computer-readable storage medium, and computer program product determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point based on the display screen's refresh rate; thus, targeted gamma correction can be performed for different refresh rates. Based on the maximum brightness value, the gamma coefficient, and the color coordinates of each gamma binding point, the target brightness value and target tristimulus value corresponding to each gamma binding point are determined; wherein, the target tristimulus values ​​include: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value; thus, the target tristimulus values ​​can be used as a reference object for gamma correction, and the correction accuracy is judged by the error between the target tristimulus values ​​and the measured tristimulus values. Preset values ​​for each gamma binding point are obtained; thus, the starting position of the gamma binding point can be accurately obtained. The more accurate the starting position, the fewer the corresponding correction iterations will be, improving the overall speed of gamma correction. A gamma binding point to be calibrated is selected. Neighboring gamma binding points are searched based on a preset value for the gamma binding point, and the measured tristimulus values ​​corresponding to these neighboring gamma binding points are obtained. Based on the error between the measured tristimulus values ​​and the target tristimulus value, the adjustment step size for each color channel is determined. This allows for targeted determination of the direction for the next gamma binding point search, improving the convergence speed of gamma calibration. The search for neighboring gamma binding points is repeated using the adjustment step size for each color channel until the error between the measured tristimulus value and the target tristimulus value for a found gamma binding point meets a preset error function threshold. At this point, the found gamma binding point is determined to be the calibrated gamma binding point. Therefore, the error of the found gamma binding point can be evaluated using the tristimulus values, effectively improving the calibration speed and ensuring that the found gamma binding point meets the preset error function threshold, thus ensuring that the brightness and color coordinates of the gamma binding point meet the requirements. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a flowchart illustrating a display screen brightness control method in one embodiment;

[0068] Figure 2 This is a flowchart illustrating the display screen brightness control method in another embodiment;

[0069] Figure 3This is a flowchart illustrating the display screen brightness control method in yet another embodiment;

[0070] Figure 4 This is a flowchart illustrating the display screen brightness control method in the fourth embodiment;

[0071] Figure 5 This is a structural block diagram of a display screen brightness control device in one embodiment;

[0072] Figure 6 This is a structural block diagram of the display screen brightness control device in another embodiment;

[0073] Figure 7 This is a structural block diagram of the display screen brightness control device in yet another embodiment;

[0074] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0076] Intuitively, when a display screen's brightness changes from black to light, one would expect the contrast between light and dark to correspond to equal intervals. However, the human eye is actually much more sensitive to brightness in darker environments than in brighter ones. Therefore, to ensure that the display effect of an AMOLED module conforms to the human eye's visual curve, gamma correction is necessary. Gamma is a parameter used to characterize the brightness response characteristics of AMOLED display devices.

[0077] In one exemplary embodiment, such as Figure 1 As shown, a display screen brightness control method is provided. When applied to AMOLED modules for gamma correction, this method may include steps 101 to 105. Wherein:

[0078] Step 101: Determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen.

[0079] In this embodiment, when the AMOLED screen is initialized and lit by the driver chip, different refresh rates can be selected, gradually evolving from the initial 60Hz to 90Hz, then to 120Hz, and even 144Hz. High refresh rate technology is crucial to the display effect of AMOLED screens, and gamma correction needs to be recalibrated at different refresh rates.

[0080] For example, after setting the refresh rate, the white point coordinates are typically selected as x = 0.305, y = 0.321; the maximum brightness is 868.11 nits. For instance, the gamma factor is generally set to 2.2, which can fluctuate according to the display specifications. Further, in some embodiments, the gamma grayscale binding points can be set sequentially as follows: [0,1,4,8,12,28,36,44,52,68,84,100,116,132,148,164,180,188,196,204,212,220,228,236,244,248,252,254,255], thus calibrating a gamma binding point value. Finally, different frequency modes can be switched to modify the gamma binding point value again, completing the calibration process for all refresh rates.

[0081] Table 1

[0082] Normal-1Gamma 868.11 nit x = 0.305, y = 0.321 Normal-2Gamma 546.32 nits x = 0.305, y = 0.321 Normal-3Gamma 310.7 nit x = 0.305, y = 0.321 Normal-4Gamma 97.53 nits x = 0.305, y = 0.321 Normal-5Gamma 97.32 nits x = 0.305, y = 0.321 Normal-6Gamma 33.57 nit x = 0.305, y = 0.321 Normal-7Gamma 11.07 nit x = 0.305, y = 0.321 Normal-8Gamma 5.56 nits x = 0.305, y = 0.321 Normal-9Gamma 2.25 nit x = 0.305, y = 0.321 HBM Gamma 1082.64 nits x = 0.305, y = 0.321

[0083] Table 1 above shows the gamma calibration and debugging scheme. As shown in Table 1, calibration is performed at 60Hz / 90Hz / 120Hz, and the debugging is as follows: 120Hz HBM---> 60Hz HBM---> 120Hz Normal1 / 60Hz Normal1--->……..---> 120Hz Normal9 / 60Hz Normal9. The 90Hz gamma is only programmed and not debugged. Finally, the following results are obtained through calculation:

[0084] 90hz gamma band=(60Hz gamma band+120Hz gamma band) / 2

[0085] Here, gamma band refers to the gamma band.

[0086] Step 102: Based on the maximum luminance value, gamma coefficient, and color coordinates of each gamma binding point, determine the target luminance value and target tristimulus value corresponding to each gamma binding point.

[0087] The target tristimulus values ​​include: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value.

[0088] In this embodiment, the target brightness value corresponding to each gamma binding point can be determined based on the relationship between grayscale and brightness, according to the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point.

[0089] For example, firstly, the grayscale value corresponding to each gamma binding point is set, wherein the brightness corresponding to the maximum grayscale value is the maximum brightness value; then, based on the grayscale value corresponding to each gamma binding point, the maximum brightness, and the gamma coefficient, the target brightness value corresponding to each gamma binding point is determined respectively.

[0090] The relationship between grayscale and brightness is as follows:

[0091]

[0092] In the formula, Lumi represents brightness, Lv represents maximum brightness value, and gray_value represents grayscale value.

[0093] For example, the target tristimulus value corresponding to each gamma binding point can be determined based on the color coordinates corresponding to each gamma binding point and the target luminance value corresponding to each gamma binding point.

[0094] The formula for calculating the target tristimulus value is as follows:

[0095]

[0096] Y = Lumi

[0097]

[0098] Where X represents the red primary color stimulus value, Y represents the green primary color stimulus value, Z represents the blue primary color stimulus value, x represents the color coordinate value on the x-axis, and y represents the color coordinate value on the y-axis.

[0099] For example, assuming the maximum brightness value is 430 nits, based on the relationship between grayscale and brightness, and the calculation formula for the target tristimulus value, we can obtain the gamma-binding grayscale value correspondence, brightness value and target tristimulus value as shown in Table 2.

[0100] Table 2

[0101]

[0102]

[0103] Step 103: Obtain the preset values ​​for each gamma binding point.

[0104] In this embodiment, the initial value of each gamma binding point, i.e. the preset value, must first be determined.

[0105] In one optional implementation, the R, G, and B channel values ​​corresponding to the largest and second largest gamma binding points can be calibrated using a color analyzer. Using these values ​​as prior conditions, the R, G, and B channel values ​​corresponding to the remaining gamma binding points are sequentially derived. The R, G, and B channel values ​​corresponding to the gamma binding points constitute the preset values ​​for the gamma binding points.

[0106] In this embodiment, the R, G, and B voltage values ​​of the 255 grayscale binding points and the 254 grayscale binding points can be calibrated using a color analyzer (CA410). Based on these prior conditions, preliminary preset values ​​for the remaining binding points are calculated. For example, for the R channel binding point voltage value, the measured actual brightness of the current binding point is lv_Current, the current binding point register value is value_current, the previous actual brightness value is lv_last, the previous binding point register value is value_last, and the next binding point target brightness value is lv_next. Then, based on the above known data, the next binding point register value value_next is calculated. The specific calculation formula is as follows:

[0107]

[0108] It should be noted that the voltage values ​​of the G channel and R channel can also be derived using the above formula, which will not be elaborated here.

[0109] Step 104: Select a gamma binding point to be calibrated, search for neighboring gamma binding points based on the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0110] In this embodiment, as shown in Table 2, different grayscale values ​​correspond to different gamma binding points. Therefore, it is necessary to correct the gamma binding points corresponding to all grayscale values.

[0111] For example, assuming the preset values ​​of the gamma grayscale binding points are R_Value, G_Value, and B_Value, the obtained measured tristimulus values ​​are X_value, Y_value, and Z_value, and the target tristimulus values ​​are X0, Y0, and Z0, the formula for calculating the error function can be obtained as follows:

[0112]

[0113] Step 105: Based on the error between the measured tristimulus values ​​and the target tristimulus values, determine the adjustment step size for each color channel.

[0114] In this embodiment, the adjustment step size of each channel of the currently searched gamma binding point can be adjusted according to the error between the measured tristimulus value and the target tristimulus value.

[0115] It should be noted that there is no one-to-one correspondence between the voltage values ​​of the R, G, and B channels of the gamma-tethered points and the target luminance values ​​and color coordinates. A change in any one of the R, G, or B channels will cause a change in all three target luminance values. Even after converting to tristimulus values, there is still no one-to-one correspondence. However, relatively speaking, there is a strong correlation: the value of the R channel of the gamma-tethered point is strongly correlated with the red primary color stimulus value X, the value of the G channel of the gamma-tethered point is strongly correlated with the green primary color stimulus value Y, and the value of the B channel of the gamma-tethered point is strongly correlated with the blue primary color stimulus value Z.

[0116] For example, if the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, the adjustment step of each color channel is set to a uniform adjustment step according to empirical parameters.

[0117] For example, if the gamma binding point to be corrected is not the largest gamma binding point or the second largest gamma binding point, the target tristimulus value and the measured tristimulus value are normalized respectively to obtain the first vector corresponding to the target tristimulus value and the second vector corresponding to the measured tristimulus value; the similarity between the first vector and the second vector is determined by the cosine function; and the adjustment step of each color channel is determined according to the similarity, the target tristimulus value, the measured tristimulus value, and the preset weight adjustment parameters.

[0118] In this embodiment, it is assumed that the gamma binding values ​​of the Gray0 grayscale are defined to be the target tristimulus values ​​(X0_target, Y0_target, Z0_target) corresponding to the maximum brightness and chromaticity. The CA410 collects the measured tristimulus values ​​(x0_measure, y0_measure, z0_measure) corresponding to the preset binding values ​​(R0_value, G0_value, B0_value) for the initial grayscale Gray0.

[0119] The target tristimulus values ​​and measured tristimulus values ​​were normalized according to the target brightness. Among them:

[0120] Normalized target tristimulus values:

[0121] Normalized measured tristimulus values:

[0122] The similarity between vector B and target vector A is calculated using the cosine function:

[0123] Right now:

[0124]

[0125] The iterative update method will be set to a variable step size. Where:

[0126] ΔR=α*(1-cosθ)*(X0_target–x0_measure);

[0127] ΔG=β*(1-cosθ)*(Y0_target–y0_measure);

[0128] ΔB=Υ*(1-cosθ)*(Z0_target–z0_measure);

[0129] α, β, and Υ are a set of weight adjustment parameters, ΔR represents the adjustment step size of the R channel, ΔG represents the adjustment step size of the G channel, and ΔB represents the adjustment step size of the B channel.

[0130] Step 106: Search for neighboring gamma binding points again by adjusting the step size of each color channel until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold. Then, determine that the currently searched gamma binding point is the corrected gamma binding point.

[0131] For example, if the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, the value of the G channel is reduced by one adjustment step; if the measured red primary stimulus value is greater than the target red primary stimulus value, the value of the R channel is reduced by one adjustment step; if the measured blue primary stimulus value is greater than the target blue primary stimulus value, the value of the B channel is reduced by one adjustment step.

[0132] In this embodiment, empirical values ​​are used for the gamma binding voltage values ​​of grayscale levels 255 and 254, and a fixed compensation iterative solution is employed. For example, based on empirical parameters, the initial gamma binding values ​​for level 255 are set as follows: R255 = 0x38C8, G255 = 0x3849, B255 = 0x3D6; the gamma binding parameter values ​​for level 254 are set as follows: R254 = 0x3869, G254 = 0x37ED, B254 = 0x3BF7. The gamma binding value of the G channel is first adjusted, with the adjustment step = 5. Then, G' = G255 - step, where G' represents the G channel value of the next searched neighboring gamma binding value, thereby ensuring that the brightness matches the target brightness value. Then adjust the values ​​of the R and B channels. For example, when step = 5, if the measured stimulus value X is too large, set R' = R - step; if the measured stimulus value Z is too large, set B' = B - step, until the chromatic coordinates x, y match the target chromatic coordinate error. Here, R' represents the R channel value of the next nearest gamma binding point found, and B' represents the B channel value of the next nearest gamma binding point found.

[0133] For example, if the gamma binding point to be corrected is not the largest gamma binding point or the second largest gamma binding point, then the values ​​of the R channel, G channel, and B channel are increased by the corresponding adjustment steps of the color channels.

[0134] In this embodiment, refer to the embodiment shown in step 105, where a new binding point value is calculated based on the target brightness and the measured value:

[0135] R'=R+ΔR

[0136] G'=G+ΔG

[0137] B'=B+ΔB

[0138] The aforementioned display screen brightness control method determines the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point based on the display screen's refresh rate, enabling targeted gamma correction for different refresh rates. Based on the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point, a target brightness value and target tristimulus value are determined for each gamma binding point. The target tristimulus values ​​include red, green, and blue primary color stimuli. These target tristimulus values ​​serve as a reference for gamma correction, and the accuracy of the correction is determined by the error between the target and measured tristimulus values. Preset values ​​for each gamma binding point are obtained, allowing for accurate determination of the starting position. A more accurate starting position reduces the number of correction iterations, thus increasing the overall speed of gamma correction. A gamma binding point to be corrected is selected, and neighboring gamma binding points are searched based on its preset value. The measured tristimulus values ​​corresponding to these neighboring gamma binding points are then obtained. Based on the error between the measured tristimulus value and the target tristimulus value, the adjustment step size for each color channel is determined. This allows for targeted determination of the direction for the next gamma binding point search, improving the convergence speed of gamma correction. The search for neighboring gamma binding points is repeated using the adjustment step size of each color channel until the error between the measured tristimulus value and the target tristimulus value corresponding to the searched gamma binding point meets a preset error function threshold. At this point, the currently searched gamma binding point is determined to be the corrected gamma binding point. Therefore, the error of the searched gamma binding point can be evaluated using the tristimulus value, effectively improving the correction speed of the gamma binding point and ensuring that the searched gamma binding point meets the preset error function threshold, thus guaranteeing that the brightness and color coordinates of the gamma binding point meet the requirements.

[0139] In another exemplary embodiment, such as Figure 2As shown, a display screen brightness control method is provided. When applied to AMOLED modules for gamma correction, this method may include steps 201 to 208. Wherein:

[0140] Step 201: Determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen.

[0141] Step 202: Based on the maximum luminance value, gamma coefficient, and color coordinates of each gamma binding point, determine the target luminance value and target tristimulus value corresponding to each gamma binding point.

[0142] The target tristimulus values ​​include: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value.

[0143] Step 203: Obtain the preset values ​​for each gamma binding point.

[0144] Step 204: Select a gamma binding point to be calibrated, search for neighboring gamma binding points based on the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0145] Step 205: Based on the error between the measured tristimulus value and the target tristimulus value, determine the adjustment step size for each color channel.

[0146] In this embodiment, please refer to the detailed implementation process and technical effects of steps 201 to 205. Figure 1 The relevant descriptions in steps 101 to 105 shown will not be repeated here.

[0147] Step 206: Determine whether the current number of searches for neighboring gamma binding points has reached the number of iterations for the binding point interval where the gamma binding point to be corrected is located. If not, proceed to step 207; if yes, proceed to step 208.

[0148] For example, as shown in Table 3, the error function threshold and number of iterations are given for different binding point intervals.

[0149] Table 3

[0150] error_β 0.001 0.002 0.004 0.01 0.05 Number of iterations 10 8 6 6 5

[0151] The values ​​in Table 3 above can be set according to the intensity of the grayscale-brightness curve changes in the bright and low brightness areas.

[0152] Step 207: By adjusting the step size of each color channel, search for neighboring gamma binding points again until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold. Then, determine that the currently searched gamma binding point is the corrected gamma binding point.

[0153] In this embodiment, please refer to the detailed implementation process and technical effects of step 207. Figure 1 The relevant descriptions in step 106 shown will not be repeated here.

[0154] Step 208: Select the gamma binding point corresponding to the optimal search value from the already searched gamma binding points as the corrected gamma binding point.

[0155] In this embodiment, the optimal search value can be: the gamma binding point corresponding to the gamma binding point whose error between the measured tristimulus value and the target tristimulus value is closest to the preset error function threshold.

[0156] In this embodiment, different search iterations can be set for different binding point intervals, thereby avoiding getting stuck in a high number of loop searches and making the gamma correction faster.

[0157] In yet another exemplary embodiment, such as Figure 3 As shown, a display screen brightness control method is provided. When applied to AMOLED modules for gamma correction, this method may include steps 301 to 308. Wherein:

[0158] Step 301: Determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen.

[0159] Step 302: Based on the maximum luminance value, gamma coefficient, and color coordinates of each gamma binding point, determine the target luminance value and target tristimulus value corresponding to each gamma binding point.

[0160] The target tristimulus values ​​include: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value.

[0161] Step 303: Obtain the preset values ​​for each gamma binding point.

[0162] Step 304: Select a gamma binding point to be calibrated, search for neighboring gamma binding points based on the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0163] Step 305: Based on the error between the measured tristimulus value and the target tristimulus value, determine the adjustment step size for each color channel.

[0164] Step 306: By adjusting the step size of each color channel, search for neighboring gamma binding points again until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold. Then, determine that the currently searched gamma binding point is the corrected gamma binding point.

[0165] In this embodiment, please refer to the detailed implementation process and technical effects of steps 301 to 306. Figure 1 The relevant descriptions in steps 101 to 106 shown will not be repeated here.

[0166] Step 307: Determine whether the calibration of all gamma binding points has been completed. If yes, end the process; otherwise, proceed to step 308.

[0167] Step 308: Select the next uncorrected gamma binding point as the gamma binding point to be corrected, and return to step 304.

[0168] In this embodiment, the gamma binding points corresponding to each grayscale value can be corrected. That is, if the correction of all gamma binding points is not completed, the next uncorrected gamma binding point is selected as the gamma binding point to be corrected; the gamma binding point to be corrected is corrected until the correction of all gamma binding points is completed. This ensures that the gamma binding points corresponding to all grayscale values ​​meet the luminance and chromaticity requirements.

[0169] In the fourth exemplary embodiment, such as Figure 4 As shown, a display screen brightness control method is provided. When applied to AMOLED modules for gamma correction, this method may include steps 401 to 406. Wherein:

[0170] Step 401: Select the initial display frequency and gamma coefficient of the screen, and set the maximum brightness, color coordinate x and color coordinate y of the gamma target value according to the gamma adjustment scheme.

[0171] Step 402: Starting from the maximum grayscale, calculate the target values ​​for all brightness levels except the maximum brightness based on the maximum brightness.

[0172] Step 403: Search for the initial preset values ​​of the maximum grayscale gamma R, G, B binding points in sequence based on the brightness and color coordinate values.

[0173] Step 404: Obtain the chromatic coordinates x and y of the gamma binding point, as well as the luminance Lv, and determine whether they are within the specified error range. If yes, proceed to step 406; otherwise, proceed to step 405.

[0174] Step 405: Convert the measured brightness and chromaticity relationship into measured tristimulus values. Calculate ΔR, ΔG, and ΔB based on the measured tristimulus values ​​and the target tristimulus values. After modifying the binding point values ​​of R, G, and B, return to step 403.

[0175] Step 406: Continue adjusting the next grayscale level until all grayscale levels meet the brightness and chromaticity requirements.

[0176] It should be noted that the gamma binding point correction method in steps 401 to 406 of this embodiment can be applied to... Figures 1-3 In the method embodiment shown, gamma correction is performed.

[0177] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0178] Based on the same inventive concept, this application also provides a display screen brightness control device for implementing the display screen brightness control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more display screen brightness control device embodiments provided below can be found in the limitations of the display screen brightness control method described above, and will not be repeated here.

[0179] In one exemplary embodiment, such as Figure 5 As shown, a display screen brightness control device is provided, including: a first determining module 501, a second determining module 502, an acquiring module 503, a searching module 504, and an adjustment step determining module 505, wherein:

[0180] The first determining module 501 is used to determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen.

[0181] The second determining module 502 is used to determine the target brightness value and target tristimulus value corresponding to each gamma binding point based on the maximum brightness value, the gamma coefficient, and the color coordinates of each gamma binding point; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value;

[0182] Module 503 is used to obtain the preset values ​​of each gamma binding point;

[0183] The search module 504 is used to select a gamma binding point to be corrected, search for neighboring gamma binding points according to the preset value of the gamma binding point to be corrected, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points.

[0184] The step size determination module 505 is used to determine the adjustment step size of each color channel based on the error between the measured tristimulus value and the target tristimulus value.

[0185] The search module 504 is further configured to re-search for neighboring gamma binding points by adjusting the step size of each color channel until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold, then the currently searched gamma binding point is determined to be the corrected gamma binding point.

[0186] For example, the second determining module 502 is specifically used to: set the grayscale value corresponding to each gamma binding point, wherein the brightness corresponding to the maximum grayscale value is the maximum brightness value;

[0187] The target brightness value corresponding to each gamma binding point is determined based on the grayscale value corresponding to each gamma binding point, the maximum brightness, and the gamma coefficient.

[0188] Based on the color coordinates and target brightness values ​​corresponding to each gamma binding point, the target tristimulus values ​​corresponding to each gamma binding point are determined.

[0189] For example, the acquisition module 503 is specifically used to: calibrate the R-channel, G-channel, and B-channel values ​​corresponding to the largest and second largest gamma binding points using a color analyzer; and, using the R-channel, G-channel, and B-channel values ​​corresponding to the largest and second largest gamma binding points as prior conditions, sequentially derive the R-channel, G-channel, and B-channel values ​​corresponding to the remaining gamma binding points; wherein the R-channel, G-channel, and B-channel values ​​corresponding to the gamma binding points constitute the preset values ​​of the gamma binding points.

[0190] For example, the adjustment step size determination module 505 is specifically used to: if the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, set the adjustment step size of each color channel to a uniform adjustment step size according to empirical parameters.

[0191] If the gamma binding point to be corrected is not the largest gamma binding point or the second largest gamma binding point, normalize the target tristimulus value and the measured tristimulus value respectively to obtain the first vector corresponding to the target tristimulus value and the second vector corresponding to the measured tristimulus value.

[0192] The similarity between the first vector and the second vector is determined by the cosine function;

[0193] The adjustment step size for each color channel is determined based on the similarity, the target tristimulus value, the measured tristimulus value, and the preset weight adjustment parameters.

[0194] For example, the search module 504 is further configured to: if the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, decrease the value of the G channel by one adjustment step; if the measured red primary color stimulus value is greater than the target red primary color stimulus value, decrease the value of the R channel by one adjustment step; if the measured blue primary color stimulus value is greater than the target blue primary color stimulus value, decrease the value of the B channel by one adjustment step.

[0195] If the gamma binding point to be corrected is not the largest or second largest gamma binding point, then increase the values ​​of the R channel, G channel, and B channel by the corresponding adjustment step of the color channel.

[0196] The various modules of the device in this embodiment can be used to implement... Figure 1 , Figure 4 Each step in the method embodiment shown.

[0197] In another exemplary embodiment, such as Figure 6 As shown, a display screen brightness control device is provided. Figure 5 Based on the device shown, it may further include: a first judgment module 506, used to: determine whether the current number of searches for neighboring gamma binding points has reached the number of iterations in the binding point interval where the gamma binding point to be corrected is located; if the number of iterations has been reached, then stop the search; select the gamma binding point corresponding to the optimal search value from the gamma binding points that have been searched as the corrected gamma binding point.

[0198] The various modules of the device in this embodiment can be used to implement... Figure 2 , Figure 4 Each step in the method embodiment shown.

[0199] In yet another exemplary embodiment, such as Figure 7 As shown, a display screen brightness control device is provided. Figure 5 Based on the device shown, it may also include:

[0200] The second judgment module 507 is used to determine whether the correction of all gamma binding points has been completed; if the correction of all gamma binding points has been completed, the process ends.

[0201] If the correction of all gamma binding points is not completed, the next uncorrected gamma binding point is selected as the gamma binding point to be corrected by the search module 504; the gamma binding point to be corrected is corrected until the correction of all gamma binding points is completed.

[0202] The various modules of the device in this embodiment can be used to implement... Figure 3 , Figure 4 Each step in the method embodiment shown.

[0203] It should be noted that if... Figures 5-7 By integrating the various modules in the device shown, it can be used to achieve... Figures 1-4 Each step in the method embodiment shown.

[0204] Each module in the aforementioned display screen brightness control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0205] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a display screen brightness control method. The display unit of the computer device forms a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0206] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0207] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0208] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0209] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0210] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0211] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0212] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0213] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling the brightness of a display screen, characterized in that, The method includes: Based on the refresh rate of the display screen, determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point; Based on the maximum luminance value, the gamma coefficient, and the color coordinates of each gamma binding point, the target luminance value and target tristimulus value corresponding to each gamma binding point are determined respectively; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value; Obtain the preset values ​​for each gamma binding point; Select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points. Based on the error between the measured tristimulus value and the target tristimulus value, the adjustment step size for each color channel is determined. This determination includes: if the gamma binding point to be corrected is neither the largest nor the second largest gamma binding point, normalizing the target tristimulus value and the measured tristimulus value to obtain a first vector corresponding to the target tristimulus value and a second vector corresponding to the measured tristimulus value; determining the similarity between the first vector and the second vector using a cosine function; and determining the adjustment step size for each color channel based on the similarity, the target tristimulus value, the measured tristimulus value, and preset weight adjustment parameters. By adjusting the step size of each color channel, the search continues to find neighboring gamma binding points until the error between the measured tristimulus value corresponding to the found gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently found gamma binding point is determined to be the corrected gamma binding point.

2. The method according to claim 1, characterized in that, The step of determining the target luminance value and target tristimulus value corresponding to each gamma binding point based on the maximum luminance value, the gamma coefficient, and the chromatic coordinates of each gamma binding point includes: Set the grayscale value corresponding to each gamma binding point, wherein the brightness corresponding to the maximum grayscale value is the maximum brightness value; The target brightness value corresponding to each gamma binding point is determined based on the grayscale value corresponding to each gamma binding point, the maximum brightness, and the gamma coefficient. Based on the color coordinates and target brightness values ​​corresponding to each gamma binding point, the target tristimulus values ​​corresponding to each gamma binding point are determined.

3. The method according to claim 1, characterized in that, The process of obtaining preset values ​​for each gamma binding point includes: The R, G, and B channel values ​​corresponding to the largest and second largest gamma binding points were determined using a color analyzer. Using the R-channel, G-channel, and B-channel values ​​corresponding to the largest and second largest gamma binding points as prior conditions, the R-channel, G-channel, and B-channel values ​​corresponding to the remaining gamma binding points are derived sequentially; wherein, the R-channel, G-channel, and B-channel values ​​corresponding to the gamma binding points constitute the preset values ​​of the gamma binding points.

4. The method according to claim 1, characterized in that, The step of determining the adjustment step size for each color channel based on the error between the measured tristimulus value and the target tristimulus value also includes: If the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, the adjustment step size of each color channel should be set to a uniform adjustment step size based on empirical parameters.

5. The method according to claim 1, characterized in that, The process of re-searching for neighboring gamma binding points by adjusting the step size of each color channel includes: If the gamma binding point to be corrected is the largest gamma binding point and the second largest gamma binding point, decrease the value of the G channel by one adjustment step; if the measured red primary stimulus value is greater than the target red primary stimulus value, decrease the value of the R channel by one adjustment step; if the measured blue primary stimulus value is greater than the target blue primary stimulus value, decrease the value of the B channel by one adjustment step. If the gamma binding point to be corrected is not the largest or second largest gamma binding point, then increase the values ​​of the R channel, G channel, and B channel by the corresponding adjustment step of the color channel.

6. The method according to any one of claims 1 to 5, characterized in that, After determining the adjustment step size for each color channel based on the error between the measured tristimulus value and the target tristimulus value, the method further includes: Determine whether the current number of searches for neighboring gamma binding points has reached the required number of iterations for the binding point interval where the gamma binding point to be corrected is located; If the number of iterations is reached, the search stops. Select the gamma binding point corresponding to the optimal search value from the already searched gamma binding points as the corrected gamma binding point.

7. The method according to any one of claims 1 to 5, characterized in that, After determining that the currently searched gamma binding point is the corrected gamma binding point, the method further includes: Determine whether the calibration of all gamma binding points has been completed; Once all gamma binding points have been calibrated, the process ends. If not all gamma binding points have been calibrated, the next uncalibrated gamma binding point is selected as the gamma binding point to be calibrated. The gamma binding points to be corrected are corrected until all gamma binding points are corrected.

8. A display screen brightness control device, characterized in that, The device includes: The first determining module is used to determine the maximum brightness value, gamma coefficient, and color coordinates of each gamma binding point according to the refresh rate of the display screen. The second determining module is used to determine the target brightness value and target tristimulus value corresponding to each gamma binding point based on the maximum brightness value, the gamma coefficient, and the color coordinates of each gamma binding point; wherein, the target tristimulus value includes: red primary color stimulus value, green primary color stimulus value, and blue primary color stimulus value; The acquisition module is used to obtain the preset values ​​of each gamma binding point; The search module is used to select a gamma binding point to be calibrated, search for neighboring gamma binding points according to the preset value of the gamma binding point to be calibrated, and obtain the measured tristimulus values ​​corresponding to the neighboring gamma binding points. The adjustment step size determination module is used to determine the adjustment step size of each color channel based on the error between the measured tristimulus value and the target tristimulus value. If the gamma binding point to be corrected is not the largest or second largest gamma binding point, the target tristimulus value and the measured tristimulus value are normalized to obtain a first vector corresponding to the target tristimulus value and a second vector corresponding to the measured tristimulus value. The similarity between the first vector and the second vector is determined by a cosine function. Based on the similarity, the target tristimulus value, the measured tristimulus value, and preset weight adjustment parameters, the adjustment step size of each color channel is determined. The search module is further configured to re-search for neighboring gamma binding points by adjusting the step size of each color channel until the error between the measured tristimulus value corresponding to the searched gamma binding point and the target tristimulus value meets the preset error function threshold. Then, the currently searched gamma binding point is determined to be the corrected gamma binding point.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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