Temperature drift compensation method of display panel and display device

Abstract

The present disclosure provides a temperature drift compensation method of a display panel and a display device. The method comprises: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; performing fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value based on the current first RGB value by the prediction function; determining whether the target display panel is under the second temperature condition, and adjusting the RGB value of the target display panel to the predicted second RGB value in response to determining that the target display panel is under the second temperature condition. According to the present disclosure, the brightness or color coordinate offset of the target display panel affected by temperature is compensated, and the display effect of the target display panel is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of display, and in particular, to a temperature drift compensation method of a display panel and a display device. BACKGROUND

[0002] This section is intended to provide background information to the embodiments of the present disclosure recited in the claims section. The description herein does not constitute admission that the information provided herein is prior art to the present disclosure.

[0003] Gamma tuning refers to the fact that the brightness perceived by the human eye and the actual display brightness of the display panel are not in a linear relationship. In a low brightness environment, the human eye is more sensitive to changes in brightness, and in a high brightness environment, the human eye is less sensitive to changes in brightness. This characteristic of the human eye is called Gamma characteristic. Due to the non-linear perception of brightness by the human eye, if a uniform change in brightness perception is required, the brightness displayed by the display panel needs to be non-uniformly changed to adapt to the Gamma characteristic of the human eye. The non-linear parameter of the brightness and the gray scale degree of the display panel can be referred to as the Gamma parameter, and the curve drawn according to the Gamma parameter is referred to as the Gamma curve. The Gamma parameter describes the non-linear relationship between brightness and gray scale, i.e., the non-linear relationship between brightness and data line input voltage. Therefore, if the brightness of the display panel does not conform to the Gamma curve described above, the display panel needs to be Gamma corrected.

[0004] In the related art, the Gamma tuning of the display panel is usually performed under normal temperature conditions. However, the actual use environment of the display device containing the display panel can be a high-temperature environment or a low-temperature environment. The display panel is greatly affected by temperature and is prone to a certain degree of brightness or color coordinate deviation, resulting in poor display effect. SUMMARY

[0005] Therefore, the purpose of the present disclosure is to provide a temperature drift compensation method of a display panel and a display device, which at least solves one of the technical problems in the related art.

[0006] To achieve the above purpose, in a first aspect, the present disclosure provides a temperature drift compensation method of a display panel, comprising:

[0007] obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to Gamma tuning under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to Gamma tuning under a second temperature condition;

[0008] fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function;

[0009] obtaining a current first RGB value of the target display panel after gamma adjustment under the first temperature condition, and predicting a second RGB value based on the current first RGB value by using the prediction function;

[0010] determining whether the target display panel is under the second temperature condition, and adjusting the RGB value of the target display panel to the predicted second RGB value in response to determining that the target display panel is under the second temperature condition.

[0011] In some example embodiments, each of the plurality of sample display panels corresponds to a plurality of luminance values, and each of the luminance values corresponds to a plurality of gray scale binding points.

[0012] Then, the obtaining of the plurality of sample first RGB values obtained by the plurality of sample display panels after gamma adjustment under the first temperature condition and the plurality of sample second RGB values obtained by the plurality of sample display panels after gamma adjustment under the second temperature condition comprises:

[0013] obtaining a sample first R value, a sample first G value, and a sample first B value in the sample first RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, and a sample second R value, a sample second G value, and a sample second B value in the sample second RGB value.

[0014] Then, the fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function comprises:

[0015] fitting the sample first R value, the sample first G value, and the sample first B value in the sample first RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, and the sample second R value, the sample second G value, and the sample second B value in the sample second RGB value to obtain a plurality of prediction functions.

[0016] In some example embodiments, the fitting based on the sample first R value, the sample first G value, and the sample first B value in the sample first RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, and the sample second R value, the sample second G value, and the sample second B value in the sample second RGB value to obtain a plurality of prediction functions comprises:

[0017] fitting a plurality of sample first R values and a plurality of sample second R values to obtain a first prediction function;

[0018] fitting based on the first G values of the samples and the second G values of the samples, to obtain a second prediction function;

[0019] fitting based on the first B values of the samples and the second B values of the samples, to obtain a third prediction function.

[0020] In some example embodiments, the fitting based on the first R values of the samples and the second R values of the samples, to obtain a first prediction function, comprises:

[0021] constructing a linear regression function based on the first R values of the samples and the second R values of the samples, the linear regression function comprising a slope parameter and an intercept parameter;

[0022] adjusting a current value of the slope parameter and a current value of the intercept parameter in the linear regression function, and predicting based on the first R values of the samples by a current linear regression function after adjusting the current value of the slope parameter and the current value of the intercept parameter, to obtain predicted second RGB values of the samples;

[0023] determining a goodness of fit of the current linear regression function based on the second R values of the samples and the predicted second RGB values of the samples, until the goodness of fit of the current linear regression function meets a preset condition, and taking the current linear regression function as the first prediction function.

[0024] In some example embodiments, the adjusting a current value of the slope parameter and a current value of the intercept parameter in the linear regression function comprises:

[0025] determining a derivative of the goodness of fit of the current linear regression function with respect to the current value of the slope parameter and the current value of the intercept parameter;

[0026] updating the current value of the slope parameter and the current value of the intercept parameter based on the derivative and a preset learning rate hyperparameter.

[0027] In some example embodiments, the determining a goodness of fit of the current linear regression function based on the second R values of the samples and the predicted second RGB values of the samples comprises:

[0028] determining a variance of the second R values of the samples and the predicted second RGB values of the samples as the goodness of fit of the current linear regression function;

[0029] the until the goodness of fit of the current linear regression function meets a preset condition, and taking the current linear regression function as the first prediction function, comprises:

[0030] until a variance of the sample second R value and the predicted sample second RGB value is minimized, the current linear regression function is taken as the first prediction function.

[0031] In some example embodiments, until a goodness of fit of the current linear regression function meets a preset condition, the current linear regression function is taken as the first prediction function, and the method further comprises:

[0032] until a variance of the sample second R value and the predicted sample second RGB value is less than or equal to a preset variance threshold, the current linear regression function is taken as the first prediction function.

[0033] In some example embodiments, after the determination of whether the target display panel is in the second temperature condition, the method further comprises:

[0034] in response to the determination that the target display panel is in a third temperature condition, the third temperature being between the first temperature and the second temperature, performing an interpolation calculation based on the current first RGB value and the predicted second RGB value to obtain a predicted third RGB value;

[0035] adjusting the RGB value of the target display panel to the predicted third RGB value.

[0036] In some example embodiments, the plurality of sample display panels and the target display panel are produced based on the same process condition.

[0037] Based on the same inventive concept, a second aspect of the example embodiments of the present disclosure provides a display device, comprising:

[0038] a display panel and a gamma adjustment device;

[0039] the gamma adjustment device is configured to determine whether the display panel is in a second temperature condition, and in response to the determination that the display panel is in the second temperature condition, adjust the RGB value of the display panel to a predicted second RGB value.

[0040] It can be seen from the above that the display panel temperature drift compensation method and display device provided by the embodiments of the present disclosure, the method comprises: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; performing fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value based on the current first RGB value by the prediction function; determining whether the target display panel is under the second temperature condition, and in response to determining that the target display panel is under the second temperature condition, adjusting the RGB value of the target display panel to the predicted second RGB value. Through the present disclosure, the brightness or color coordinate offset of the target display panel affected by temperature is compensated, and the display effect of the target display panel is improved. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present disclosure or the related art, the drawings needed to be used in the embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are only embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor.

[0042] Figure 1 A flowchart of a display panel temperature drift compensation method provided by an exemplary embodiment of the present disclosure is shown.

[0043] Figure 2 A schematic diagram of a fitting method provided by an exemplary embodiment of the present disclosure is shown.

[0044] Figure 3 Another schematic diagram of a fitting method provided by an exemplary embodiment of the present disclosure is shown.

[0045] Figure 4 A schematic diagram of a gamma curve without applying the scheme of the present disclosure is shown.

[0046] Figure 5 A schematic diagram of a gamma curve applying the scheme of the present disclosure is shown.

[0047] Figure 6 A structural schematic diagram of an electronic device provided by an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0048] To make the objects, technical solutions and advantages of the present disclosure clearer, the principles and spirits of the present disclosure will be described below with reference to several exemplary embodiments. It should be understood that the embodiments are merely used to enable those skilled in the art to have a better understanding and to implement the present disclosure, and do not limit the scope of the present disclosure in any way. On the contrary, the embodiments are provided to make the present disclosure more thorough and complete, and to enable the scope of the present disclosure to be fully conveyed to those skilled in the art.

[0049] In this document, it should be understood that the number of any elements in the accompanying drawings is merely used for example, rather than limitation, and any naming is merely used for differentiation, without any limiting meaning.

[0050] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should be understood as the common meanings thereof by those skilled in the art to which the present disclosure belongs. The terms "first", "second" and similar terms used in the embodiments of the present disclosure do not represent any order, number or importance, but are merely used to distinguish different components. The terms "include", "contain" and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, without excluding other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right" and the like are merely used to represent relative positional relationships, and when the absolute positions of the described objects are changed, the relative positional relationships can also be changed accordingly. The article "a" or "an" before an element does not exclude the existence of multiple such elements.

[0051] The principles and spirits of the present disclosure will be described in detail below with reference to several representative embodiments of the present disclosure.

[0052] Gamma tuning refers to the fact that the brightness perceived by the human eye and the actual display brightness of the display panel are not in a linear relationship. In a low brightness environment, the human eye is more sensitive to the change of brightness, and in a high brightness environment, it is the opposite. This characteristic of the human eye is called Gamma characteristic. Due to the non-linear perception of brightness by the human eye, if a uniform change in brightness perception is required, the brightness displayed by the display panel needs to be non-uniformly changed to adapt to the Gamma characteristic of the human eye. The non-linear parameter of the brightness and the gray scale degree of the display panel can be referred to as the Gamma parameter, and the curve drawn according to the Gamma parameter is referred to as the Gamma curve. The Gamma parameter describes the non-linear relationship between brightness and gray scale, i.e. the non-linear relationship between brightness and data line input voltage. Therefore, if the brightness of the display panel and the data line input voltage do not conform to the Gamma curve described above, the display panel needs to be Gamma corrected.

[0053] In the related art, gamma adjustment is usually performed on a display panel under normal temperature conditions (for example, at 20-25 DEG C). However, the inventors of the present disclosure have found that the actual use environment of a display device including the display panel can be a high-temperature environment (for example, at 40-50 DEG C) or a low-temperature environment (for example, at 0- -10 DEG C), and the display panel is greatly affected by temperature (for example, affected by high or low temperature of a circuit or a light-emitting device), and is prone to a certain degree of brightness or color coordinate deviation, resulting in poor display effect.

[0054] To solve the above problems, the present disclosure provides a temperature drift compensation scheme for a display panel, specifically comprising: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value based on the current first RGB value by the prediction function; determining whether the target display panel is under the second temperature condition, and in response to determining that the target display panel is under the second temperature condition, adjusting the RGB value of the target display panel to the predicted second RGB value.

[0055] In specific implementation, the prediction function between the RGB value under normal temperature conditions and the RGB value under high temperature (or low temperature, hereinafter described with high temperature, and the same applies to low temperature) conditions is obtained by fitting based on the RGB value of the sample display panel under normal temperature conditions and the RGB value under high temperature conditions. Then, the prediction function is written into the gamma adjustment device corresponding to the target display panel, and after the target display panel is subjected to gamma adjustment under normal temperature conditions, the RGB value of the target display panel under normal temperature conditions is obtained, and the RGB value under high temperature conditions is obtained by calculating based on the RGB value under normal temperature conditions and the prediction function, and is stored in the gamma adjustment device corresponding to the target display panel. Finally, in the actual use process of the display device including the target display panel, when the target display panel is under high temperature conditions, the RGB value of the target display panel is adjusted to the RGB value under high temperature conditions stored in the gamma adjustment device corresponding to the target display panel. The RGB value is used to affect brightness or color coordinates. Specifically, brightness can be calculated by weighted sum of RGB values; RGB values can be converted to color coordinates by conversion formula, so as to compensate for the brightness or color coordinate deviation of the target display panel affected by temperature, and improve the display effect of the target display panel.

[0056] After introducing the basic principles of the present disclosure, various non-limiting embodiments of the present disclosure will be specifically introduced below. It should be noted that the above application scenarios are only shown for the purpose of facilitating the understanding of the spirit and principles of the present disclosure, and the embodiments of the present disclosure are not limited in this respect. On the contrary, the embodiments of the present disclosure can be applied to any applicable scenario.

[0057] Reference Figure 1 FIG. 1 is a flow diagram of a method for compensating for temperature drift of a display panel according to an example embodiment of the present disclosure.

[0058] The method for compensating for temperature drift of a display panel comprises the following steps:

[0059] In step S110, a plurality of sample first RGB values obtained after gamma adjustment of a plurality of sample display panels under a first temperature condition and a plurality of sample second RGB values obtained after gamma adjustment of the plurality of sample display panels under a second temperature condition are acquired.

[0060] In some example embodiments, the plurality of sample display panels are produced based on the same process condition.

[0061] In specific implementation, a plurality of display panels produced in the same batch are selected as the sample display panels.

[0062] In the above formula, the plurality of sample display panels are produced based on the same process condition. In comparison with display panels produced under different process conditions, display panels produced under the same process condition have smaller differences. Therefore, the accuracy of the prediction function fitted based on the data of the display panels produced under the same process condition is higher, and the accuracy of the gamma adjustment of the display panel is higher.

[0063] In specific implementation, a certain number of display panels are selected as the sample display panels.

[0064] In the above formula, the more the number of the sample display panels, the higher the accuracy of the prediction function fitted, and the higher the accuracy of the gamma adjustment of the display panel.

[0065] In some example embodiments, the sample display panel and the target display panel are produced based on the same process condition.

[0066] In the embodiment, the sample display panel used to obtain the prediction function and the target display panel to which the prediction function is applied have the same production process conditions, thereby improving the accuracy of the gamma adjustment of the target display panel.

[0067] In some example embodiments, the first temperature condition comprises a normal temperature condition, and the second temperature condition comprises a high temperature condition or a low temperature condition.

[0068] As an example, the normal temperature condition comprises 20-25℃.

[0069] The high temperature condition comprises 40-50℃.

[0070] The low temperature condition comprises 0- -10℃.

[0071] In some example embodiments, each sample display panel of the plurality of sample display panels corresponds to a plurality of luminance values, and each luminance value corresponds to a plurality of gray scale binding points.

[0072] The obtaining of the plurality of sample first RGB values obtained after the gamma adjustment of the plurality of sample display panels under the first temperature condition and the plurality of sample second RGB values obtained after the gamma adjustment of the plurality of sample display panels under the second temperature condition comprises:

[0073] The sample first R value, the sample first G value, the sample first B value in the sample first RGB value corresponding to each gray scale binding point corresponding to each luminance value corresponding to each sample display panel of the plurality of sample display panels, and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value.

[0074] In the embodiment, the obtaining of the plurality of sample first RGB values obtained after the gamma adjustment of the plurality of sample display panels under the first temperature condition and the plurality of sample second RGB values obtained after the gamma adjustment of the plurality of sample display panels under the second temperature condition comprises the following steps:

[0075] In step S210, the plurality of sample display panels are subjected to the gamma adjustment under the first temperature condition, and the sample first RGB value of each sample display panel of the plurality of sample display panels is obtained.

[0076] In the embodiment, the first temperature condition comprises a normal temperature condition, for example, one temperature in 20-25℃.

[0077] In implementation, the RGB values of the display panel are stored in a register, and the sample first RGB values of each sample display panel are obtained from the register.

[0078] In implementation, the R value, the G value and the B value in the RGB values of the display panel are respectively stored in separate registers, and the first R value, the first G value and the first B value in the sample first RGB values of each sample display panel are obtained from the three registers.

[0079] In implementation, the display panel has a plurality of luminances, each luminance corresponds to a plurality of binding points, and the sample first RGB values include the R value, the G value and the B value of each binding point under each luminance.

[0080] In step S220, gamma adjustment is performed on the plurality of sample display panels under the second temperature condition to obtain sample second RGB values of each sample display panel in the plurality of sample display panels.

[0081] In implementation, the second temperature condition includes a high temperature condition, for example, one temperature in 40-50℃, and the second temperature condition includes a low temperature condition, for example, one temperature in 0- -10℃.

[0082] In implementation, the sample display panel is placed on a platform providing the second temperature condition, heated or cooled to the second temperature, and then gamma adjustment is performed to obtain the sample second RGB values. In this gamma adjustment, a stricter gamma adjustment standard is adopted to improve the accuracy of the obtained sample second RGB values, improve the accuracy of the predicted function obtained by fitting, and improve the accuracy of the gamma adjustment of the display panel.

[0083] In implementation, the RGB values of the display panel are stored in a register, and the sample second RGB values of each sample display panel are obtained from the register.

[0084] In implementation, the R value, the G value and the B value in the RGB values of the display panel are respectively stored in separate registers, and the second R value, the second G value and the second B value in the sample second RGB values of each sample display panel are obtained from the three registers.

[0085] In implementation, the display panel has a plurality of luminances, each luminance corresponds to a plurality of binding points, and the sample second RGB values include the R value, the G value and the B value of each binding point under each luminance.

[0086] In step S120, fitting is performed based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a predicted function.

[0087] In some example embodiments, each of the sample display panels corresponds to a plurality of luminance values, each of the luminance values corresponding to a plurality of gray scale binding points;

[0088] Then, the fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function comprises:

[0089] Fitting the sample first R value, the sample first G value, the sample first B value in the sample first RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value to obtain a plurality of prediction functions.

[0090] In some example embodiments, the fitting based on the sample first R value, the sample first G value, the sample first B value in the sample first RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value to obtain a plurality of prediction functions comprises:

[0091] Fitting a plurality of the sample first R values and a plurality of the sample second R values to obtain a first prediction function;

[0092] Fitting a plurality of the sample first G values and a plurality of the sample second G values to obtain a second prediction function;

[0093] Fitting a plurality of the sample first B values and a plurality of the sample second B values to obtain a third prediction function.

[0094] In implementation, reference is made to Figure 2 which is a visualization representation of the fitting result based on fitting one channel (R value, G value or B value) in RGB.

[0095] In implementation, reference is made to Figure 3 The display panel has a plurality of luminances, each of the luminances corresponding to a plurality of binding points, and for each color channel (R value, G value or B value) in the RGB value of each binding point under each luminance, a prediction function is obtained by fitting respectively.

[0096] In some example embodiments, the fitting of a plurality of the sample first R values and a plurality of the sample second R values to obtain a first prediction function comprises:

[0097] A linear regression function is constructed based on the sample first R value and the sample second R value, and the linear regression function includes a slope parameter and an intercept parameter.

[0098] adjusting a current value of the slope parameter and a current value of the intercept parameter in the linear regression function, predicting a predicted sample second RGB value based on the sample first R value by a current linear regression function after adjusting the current value of the slope parameter and the current value of the intercept parameter;

[0099] determining a goodness of fit of the current linear regression function based on the sample second R value and the predicted sample second RGB value, until the goodness of fit of the current linear regression function meets a preset condition, taking the current linear regression function as the first prediction function.

[0100] In some example embodiments, the adjusting the current value of the slope parameter and the current value of the intercept parameter in the linear regression function comprises:

[0101] determining a derivative of the goodness of fit of the current linear regression function with respect to the current value of the slope parameter and the current value of the intercept parameter;

[0102] updating the current value of the slope parameter and the current value of the intercept parameter based on the derivative and a preset learning rate hyperparameter.

[0103] In some example embodiments, the determining the goodness of fit of the current linear regression function based on the sample second R value and the predicted sample second RGB value comprises:

[0104] determining a variance of the sample second R value and the predicted sample second RGB value as the goodness of fit of the current linear regression function;

[0105] The until the goodness of fit of the current linear regression function meets the preset condition, taking the current linear regression function as the first prediction function comprises:

[0106] until the variance of the sample second R value and the predicted sample second RGB value is minimized, taking the current linear regression function as the first prediction function.

[0107] In some example embodiments, the until the goodness of fit of the current linear regression function meets the preset condition, taking the current linear regression function as the first prediction function further comprises:

[0108] until the variance of the sample second R value and the predicted sample second RGB value is less than or equal to a preset variance threshold, taking the current linear regression function as the first prediction function.

[0109] In specific implementation, taking the linear regression as an example in a fitting manner, the prediction function is constructed as:

[0110] First temperature REGR * R second temperature coefficient + bias value = second temperature REGR;

[0111] First temperature REGB * B second temperature coefficient + bias value = second temperature REGB;

[0112] First temperature REGG * G second temperature coefficient + bias value = second temperature REGG;

[0113] In specific implementation, when the first temperature is normal temperature, and the second temperature is high temperature or low temperature, the prediction function is:

[0114] Normal temperature REGR * R high / low temperature coefficient + bias value = high / low temperature REGR;

[0115] Normal temperature REGB * B high / low temperature coefficient + bias value = high / low temperature REGB;

[0116] Normal temperature REGG * G high / low temperature coefficient + bias value = high / low temperature REGG.

[0117] Wherein, REGR represents the R value in the register, REG represents the register, the register is a small high-speed storage device for storing and processing data, which is usually directly connected with the CPU closely, and is used for storing temporary data, address and control information, etc. Similarly, REGB represents the B value in the register, and REGG represents the G value in the register.

[0118] In specific implementation, at the beginning of fitting, the second temperature coefficient (high / low temperature coefficient) and the bias value are both set to 0, the increment / decrement of each fitting is ±0.001 (which can be adjusted according to actual situation), and after each fitting is completed, the loss (Loss) is obtained by calculating the variance of the predicted second RGB value (predicted value) and the sample second RGB value (actual value) of each prediction function. When the loss no longer decreases, the parameters of the prediction function obtained at this time are the expected optimal solution.

[0119] In order to evaluate the result of fitting, the loss function is established as above. In linear regression, the loss function is the variance of the function predicted value and the actual value (the loss function under linear regression has a definite minimum point, so as to avoid that the linear regression function falls into a local optimal solution). In each iteration of the prediction function, the corresponding loss is calculated. When the loss reaches the minimum value, the prediction function at this time is the global optimal solution of the collected data. By establishing the loss function, it can be ensured that the obtained prediction function is the optimal solution of the current data, so as to improve the prediction accuracy and enhance the compensation effect. By observing the final loss value, it can also be judged whether the collected data and the fitted model are accurate, so as to decide whether the data needs to be collected again or the fitting parameters need to be adjusted.

[0120] In specific implementation, the gradient descent algorithm can be used when fitting to improve the fitting speed, and when the data amount is large, the fitting time can be saved.

[0121] The gradient descent algorithm is an iterative method that can be used to solve least squares problems (both linear and nonlinear) to solve model parameters of machine learning algorithms, i.e., when solving unconstrained optimization problems.

[0122] It should be noted that in addition to linear regression, other types of fitting methods can be used when fitting, and appropriate fitting methods can be selected according to the characteristics and distribution of the data.

[0123] In step S130, the current first RGB value of the target display panel after gamma adjustment under the first temperature condition is obtained, and the prediction function is used to predict the current first RGB value to obtain the predicted second RGB value.

[0124] In specific implementation, the prediction function obtained by fitting is written into the gamma adjustment device corresponding to the target display panel. After the target display panel is gamma adjusted under normal temperature conditions, the RGB value of the target display panel under normal temperature conditions is obtained. The prediction function is used to predict the RGB value under normal temperature conditions to obtain the RGB value under high / low temperature conditions, which is stored in the gamma adjustment device corresponding to the target display panel.

[0125] In specific implementation, the gamma adjustment device includes a register and a chip (CPU). The register is a small high-speed storage device for storing and processing data, which is usually directly connected to the CPU and used to store temporary data, addresses, and control information.

[0126] In step S140, it is determined whether the target display panel is under the second temperature condition. In response to determining that the target display panel is under the second temperature condition, the RGB value of the target display panel is adjusted to the predicted second RGB value.

[0127] In specific implementation, in the actual use process of the display device containing the target display panel, when the target display panel is under high / low temperature conditions, the RGB value of the target display panel is adjusted to the RGB value under high / low temperature conditions stored in the gamma adjustment device corresponding to the target display panel, which compensates for the brightness or color coordinate offset of the target display panel when affected by temperature, and improves the display effect of the target display panel.

[0128] In the above exemplary embodiments, the first temperature condition includes a normal temperature condition, such as one of 20℃ to 25℃, and the second temperature condition includes a high temperature condition or a low temperature condition, such as one of 40℃ to 50℃ or one of 0℃ to -10℃, however, the present disclosure is not limited thereto, and the present disclosure can be applied to multiple target temperatures in addition to one target temperature, including at least the following two ways:

[0129] As an example, if the display device containing the target display panel is in a situation of being at both 40℃ and 0℃ in actual use, the predicted RGB values are determined based on 40℃ and 0℃ respectively, and are stored in the gamma adjustment device corresponding to the target display panel, and the predicted RGB values are called when at the corresponding temperature.

[0130] As an example, if the first temperature is 20℃ and the second temperature is 40℃, and the display device containing the target display panel is in a temperature condition between 20℃ and 40℃ in actual use, then:

[0131] In response to determining that the target display panel is at a third temperature condition, the third temperature being between the first temperature and the second temperature, an interpolation calculation is performed based on the current first RGB value and the predicted second RGB value to obtain a predicted third RGB value;

[0132] The RGB value of the target display panel is adjusted to the predicted third RGB value.

[0133] Reference Figure 4 , which is the gamma curve of the display panel in the related art, i.e., the gamma curve without applying the scheme of the present disclosure; reference Figure 5 , which is the gamma curve after applying the scheme of the present disclosure.

[0134] Wherein, the ideal Gamma curve should be a straight line, but in fact, due to the physical limitations of display equipment, the curve is often nonlinear. Although there is no uniform standard for the Gamma value of a display, most displays follow 2.2 as the recommended Gamma value.

[0135] As shown in Figure 4 , the gamma curve without applying the scheme of the present disclosure, especially when the gray scale value is low, the gamma curve deviates far from 2.2, and as shown in Figure 5 , the gamma curve after applying the scheme of the present disclosure, the gamma parameter is around 2.2, close to a straight line.

[0136] It can be seen from the above that the temperature drift compensation method of the display panel provided by the embodiments of the present disclosure includes: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; performing fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value based on the current first RGB value by using the prediction function; determining whether the target display panel is under the second temperature condition, and adjusting the RGB value of the target display panel to the predicted second RGB value in response to determining that the target display panel is under the second temperature condition.

[0137] Through the present disclosure, the RGB value is used to affect the brightness or the color coordinate. Specifically, the brightness can be calculated by weighted summation of the RGB value. The RGB value can be converted into the color coordinate by the conversion formula, which compensates for the brightness or color coordinate offset of the target display panel affected by the temperature, and improves the display effect of the target display panel.

[0138] By collecting the target temperature Gamma register value to separately calculate a Gamma curve for the target temperature instead of the related art light-emitting material voltage, the compensation effect is significant.

[0139] By using the linear regression algorithm with the loss function to process the collected Gamma data, the problem of low accuracy and difficulty in quantifying the accuracy when manually determining the compensation coefficient in the related art is avoided. The fitting result is ensured to be the optimal solution to the greatest extent, and the gradient descent algorithm is used to optimize the fitting time, which has good performance when the data volume is large. The large data model makes the fitting result better on the batch products, and greatly improves the accuracy of compensation.

[0140] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server. The method of the present embodiment can also be applied to a distributed scenario, and completed by multiple devices cooperating with each other. In this distributed scenario, one of the multiple devices can only execute one or more steps in the method of the present disclosure, and the multiple devices will interact with each other to complete the method.

[0141] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims can be performed in a different order than those described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0142] Based on the same inventive concept, the present disclosure also provides a display device corresponding to any of the above-mentioned embodiment methods.

[0143] The display device comprises:

[0144] The display panel and a gamma adjustment device.

[0145] The gamma adjustment device is configured to determine whether the display panel is in a second temperature condition, and in response to determining that the display panel is in the second temperature condition, adjust the RGB value of the display panel to a predicted second RGB value.

[0146] For the convenience of description, the above device is described in various modules according to functions. Of course, in the implementation of the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0147] The device of the above-mentioned embodiment is used to implement the temperature drift compensation method of the corresponding display panel in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be described here.

[0148] Based on the same inventive concept, the present disclosure also provides an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the temperature drift compensation method of the display panel according to any of the above-mentioned embodiments.

[0149] Figure 6 A more specific hardware structure schematic diagram of an electronic device provided by the present embodiment is shown, which can include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040 and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030 and the communication interface 1040 are connected to each other through the bus 1050 for communication within the device.

[0150] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., for executing relevant programs to implement the technical solutions provided by the embodiments of the present specification.

[0151] The memory 1020 can be implemented by a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0152] The input / output interface 1030 is configured to connect input / output modules to implement information input and output. The input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input devices can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices can include a display, a speaker, a vibrator, an indicator light, etc.

[0153] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to implement the communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as USB, network cable, etc.) or through a wireless manner (such as mobile network, WIFI, Bluetooth, etc.).

[0154] The bus 1050 includes a channel for transmitting information between various components (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0155] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only include the components necessary to implement the solutions of the embodiments of the present specification, and does not have to include all the components shown in the figure.

[0156] The electronic device of the above embodiment is used to implement the temperature drift compensation method of the display panel in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described here again.

[0157] The memory 1020 stores machine-readable instructions executable by the processor 1010. When the electronic device is running, the processor 1010 communicates with the memory 1020 through the bus 1030, so that the processor 1010 executes the following instructions when running:

[0158] obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition;

[0159] fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function;

[0160] obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value based on the current first RGB value by the prediction function;

[0161] determining whether the target display panel is under the second temperature condition, and adjusting the RGB value of the target display panel to the predicted second RGB value in response to determining that the target display panel is under the second temperature condition.

[0162] In a possible implementation, in the instructions executed by the processor 1010, each sample display panel in the plurality of sample display panels corresponds to a plurality of luminance values, and each luminance value corresponds to a plurality of gray scale binding points;

[0163] Therefore, the obtaining of the plurality of sample first RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under the first temperature condition and the plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under the second temperature condition comprises:

[0164] obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition;

[0165] Therefore, the fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function comprises:

[0166] fitting the sample first R value, the sample first G value, the sample first B value in the sample first RGB value and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, to obtain a plurality of prediction functions.

[0167] In a possible implementation, in the instructions executed by the processor 1010, the fitting the sample first R value, the sample first G value, the sample first B value in the sample first RGB value and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, to obtain a plurality of prediction functions, comprises:

[0168] fitting the plurality of sample first R values and the plurality of sample second R values to obtain a first prediction function;

[0169] fitting the plurality of sample first G values and the plurality of sample second G values to obtain a second prediction function;

[0170] fitting the plurality of sample first B values and the plurality of sample second B values to obtain a third prediction function.

[0171] In a possible implementation, in the instructions executed by the processor 1010, the fitting the plurality of sample first R values and the plurality of sample second R values to obtain a first prediction function, comprises:

[0172] constructing a linear regression function based on the sample first R value and the sample second R value, the linear regression function comprising a slope parameter and an intercept parameter;

[0173] adjusting a current value of the slope parameter and a current value of the intercept parameter in the linear regression function, and predicting a predicted sample second RGB value based on the sample first R value by using a current linear regression function after the adjustment of the current value of the slope parameter and the current value of the intercept parameter;

[0174] determining a goodness of fit of the current linear regression function based on the sample second R value and the predicted sample second RGB value, until the goodness of fit of the current linear regression function meets a preset condition, and taking the current linear regression function as the first prediction function.

[0175] In a possible implementation, in the instructions executed by the processor 1010, the adjusting a current value of the slope parameter and a current value of the intercept parameter in the linear regression function, comprises:

[0176] determining a derivative of the goodness of fit of the current linear regression function with respect to the current value of the slope parameter and the current value of the intercept parameter;

[0177] updating the current value of the slope parameter and the current value of the intercept parameter based on the derivative and a preset learning rate hyperparameter.

[0178] In a possible implementation, the instructions executed by the processor 1010, in determining the goodness of fit of the current linear regression function based on the sample second R value and the predicted sample second RGB value, include:

[0179] determining a variance of the sample second R value and the predicted sample second RGB value as the goodness of fit of the current linear regression function;

[0180] the instructions executed by the processor 1010, in determining the goodness of fit of the current linear regression function until the goodness of fit of the current linear regression function meets a preset condition, include:

[0181] the instructions executed by the processor 1010, in determining the goodness of fit of the current linear regression function until the goodness of fit of the current linear regression function meets a preset condition, include:

[0182] In a possible implementation, the instructions executed by the processor 1010, in determining the goodness of fit of the current linear regression function until the goodness of fit of the current linear regression function meets a preset condition, further include:

[0183] the instructions executed by the processor 1010, in determining the goodness of fit of the current linear regression function until the goodness of fit of the current linear regression function meets a preset condition, further include:

[0184] In a possible implementation, the instructions executed by the processor 1010, after determining whether the target display panel is in the second temperature condition, the method further includes:

[0185] in response to determining that the target display panel is in a third temperature condition, the third temperature being between the first temperature and the second temperature, performing interpolation calculation based on the current first RGB value and the predicted second RGB value to obtain a predicted third RGB value;

[0186] adjusting the RGB value of the target display panel to the predicted third RGB value.

[0187] Based on the same inventive concept, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the display panel temperature drift compensation method according to any of the above embodiments.

[0188] The computer-readable medium of the present embodiment includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0189] The above-mentioned non-transitory computer-readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disk, hard disk, magnetic tape, magneto-optical disk (MO) and the like), optical storage (such as CD, DVD, BD, HVD and the like), and semiconductor memory (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid state disk (SSD)) and the like.

[0190] The storage medium of the above-mentioned embodiment stores computer instructions for causing the computer to perform the display panel temperature drift compensation method according to any of the above-mentioned exemplary method embodiments, and has the beneficial effects of the corresponding method embodiments, which are not repeated here.

[0191] Based on the same inventive concept, the present disclosure also provides a computer program product including computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer to cause the computer and / or the processor to perform the display panel temperature drift compensation method. The processor performing the corresponding steps can belong to the corresponding execution subject corresponding to each step in each embodiment of the display panel temperature drift compensation method.

[0192] The computer program product of the above embodiments is used to make the computer and / or the processor execute the temperature drift compensation method of the display panel as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described herein again.

[0193] Those skilled in the art know that the embodiments of the present disclosure can be implemented as a system, a method, or a computer program product. Therefore, the present disclosure can be embodied in the form of entire hardware, entire software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, which are generally referred to as "circuitry", "module" or "system" herein. In addition, in some embodiments, the present disclosure can also be embodied in the form of a computer program product in one or more computer readable media, which contains computer readable program codes.

[0194] Any combination of one or more computer readable medium can be employed. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the above. More specific examples (non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0195] The computer readable signal medium can include a data signal propagated in baseband or propagated as a carrier wave in a propagated data signal, in which the computer readable program code is contained. Such propagated data signal can take many forms, including but not limited to electro-magnetic signal, optical signal, or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium that can send, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or device.

[0196] The program code contained in the computer readable medium can be transmitted in any suitable medium, including but not limited to wireless, wireline, optical cable, RF, etc., or any suitable combination of the above.

[0197] Computer program code for carrying out operations of the present disclosure can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0198] It should be understood that each block of the flowchart and / or block diagram illustrations, and combinations of blocks in the flowchart and / or block diagram illustrations, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0199] These computer program instructions can also be stored in a computer readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0200] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0201] Further, while operations of the present disclosure are described in a particular order in the figures, it is not necessary to perform the operations in the particular order shown, or in all of the operations shown, to achieve desirable results. Rather, the order of operations can be changed, some operations can be performed in parallel, and / or some operations can be omitted, combined, and / or performed separately from other operations.

[0202] The computer program product of the present application can be a computer program product comprising a computer readable storage medium and a computer program mechanism embedded in the computer readable storage medium. Such computer program product can further include computer readable storage medium and / or computer program mechanism.

[0203] It should be noted that while the foregoing describes a number of modules or units of the device for action execution, this division into modules or units is not mandatory. Indeed, according to the embodiments of the application, the features and functionalities of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functionalities of one module or unit described above can be further divided into a plurality of modules or units.

[0204] It should be understood by those of ordinary skill in the art that the above discussion of any of the embodiments is merely exemplary in nature and is not intended to imply limitations on the scope of the application, including the claims. Various modifications can be made to the embodiments and / or different combinations of technical features from different embodiments can be selected that fall within the scope of the application as described above. In order to simplify the description and discussion, and in order not to make the embodiments of the application difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components can or can not be shown in the provided drawings. Furthermore, devices can be shown in block diagram form in order to avoid making the embodiments of the application difficult to understand, and this also takes into account the fact that the details regarding the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the application are to be implemented (i.e., these details should be well within the understanding of those skilled in the art). Where specific details (e.g., a circuit) are set forth in order to describe an illustrative embodiment of the application, it should be understood that the embodiment of the application can be practiced without these specific details, or with substitution of one or more equivalent embodiments or elements, as would be apparent to those skilled in the art. Therefore, the description should not be taken to be limiting in nature.

[0205] Furthermore, devices can be shown in block diagram form in order to avoid making the embodiments of the application difficult to understand, and this also takes into account the fact that the details regarding the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the application are to be implemented (i.e., these details should be well within the understanding of those skilled in the art). Where specific details (e.g., a circuit) are set forth in order to describe an illustrative embodiment of the application, it should be understood that the embodiment of the application can be practiced without these specific details, or with substitution of one or more equivalent embodiments or elements, as would be apparent to those skilled in the art. Therefore, the description should not be taken to be limiting in nature.

[0206] While the present application has been described in connection with certain embodiments thereof, many modifications, substitutions, and alterations, thereof, will be apparent to those of ordinary skill in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) can use the embodiments discussed.

[0207] It is intended that the embodiments of the present application encompass all such substitutions, modifications and alterations that fall within the broadest possible scope of the appended claims. Accordingly, any and all such modifications, alterations, permutations or equivalents that fall within the true spirit and scope of the embodiments of the present application should be included within the scope of the claims.

[0208] While the principles of the disclosure have been described above in connection with specific embodiments, it is to be understood that this disclosure is not limited to the disclosed embodiments, but is instead applicable to various modifications and equivalent arrangements. The scope of the disclosure encompasses various modifications and equivalent arrangements. The scope of the claims appended hereto is intended to include all such modifications and equivalent arrangements.

Claims

1. A temperature drift compensation method of a display panel, characterized in that, The method comprises: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; the sample first RGB values comprise sample first R values, and the sample second RGB values comprise sample second R values; performing fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; the prediction function comprises a first prediction function, wherein a linear regression function is constructed based on the sample first R values and the sample second R values, the linear regression function comprises a slope parameter and an intercept parameter, a derivative of a goodness of fit of a current linear regression function with respect to a current value of the slope parameter and a current value of the intercept parameter is determined, the current value of the slope parameter and the current value of the intercept parameter are updated based on the derivative and a preset learning rate hyperparameter, a predicted sample second RGB value is obtained by predicting based on the sample first R values by using the current linear regression function after the current value of the slope parameter and the current value of the intercept parameter are adjusted, and the goodness of fit of the current linear regression function is determined based on the sample second R values and the predicted sample second RGB values until the goodness of fit of the current linear regression function meets a preset condition, and the current linear regression function is taken as the first prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value by predicting based on the current first RGB value by using the prediction function; determining whether the target display panel is under the second temperature condition, and adjusting an RGB value of the target display panel to the predicted second RGB value in response to a determination that the target display panel is under the second temperature condition.

2. The method of claim 1, wherein, each sample display panel in the plurality of sample display panels corresponds to a plurality of luminance values, and each luminance value corresponds to a plurality of gray scale binding points; the obtaining of the plurality of sample first RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under the first temperature condition and the plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under the second temperature condition comprises: obtaining sample first R values, sample first G values, sample first B values in the sample first RGB values and sample second R values, sample second G values, sample second B values in the sample second RGB values corresponding to each gray scale binding point corresponding to each luminance value corresponding to each sample display panel in the plurality of sample display panels; the performing of fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function comprises: fitting the sample first R value, the sample first G value, the sample first B value in the sample first RGB value and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, to obtain a plurality of prediction functions.

3. The method of claim 2, wherein, The prediction functions further include a second prediction function and a third prediction function, and the fitting the sample first R value, the sample first G value, the sample first B value in the sample first RGB value and the sample second R value, the sample second G value, the sample second B value in the sample second RGB value corresponding to each of the gray scale binding points corresponding to each of the luminance values corresponding to each of the sample display panels in the plurality of sample display panels, to obtain a plurality of prediction functions, includes: fitting a plurality of the sample first G values and a plurality of the sample second G values to obtain a second prediction function; fitting a plurality of the sample first B values and a plurality of the sample second B values to obtain a third prediction function.

4. The method of claim 1, wherein, The determining the goodness of fit of the current linear regression function based on the sample second R value and the predicted sample second RGB value includes: determining the variance of the sample second R value and the predicted sample second RGB value as the goodness of fit of the current linear regression function; The until the goodness of fit of the current linear regression function meets a preset condition, the current linear regression function is taken as the first prediction function, includes: until the variance of the sample second R value and the predicted sample second RGB value is minimized, the current linear regression function is taken as the first prediction function.

5. The method of claim 4, wherein, The until the goodness of fit of the current linear regression function meets a preset condition, the current linear regression function is taken as the first prediction function, further includes: until the variance of the sample second R value and the predicted sample second RGB value is less than or equal to a preset variance threshold, the current linear regression function is taken as the first prediction function.

6. The method of claim 1, wherein, The method further includes: in response to determining that the target display panel is in a third temperature condition, the third temperature being between the first temperature and the second temperature, performing interpolation calculation based on the current first RGB value and the predicted second RGB value to obtain a predicted third RGB value; adjusting the RGB value of the target display panel to the predicted third RGB value.

7. The method of claim 1, wherein, The plurality of sample display panels and the target display panel are produced based on the same process conditions.

8. A display device, characterized by comprising: includes: a display panel and a gamma adjustment device; The gamma adjustment device is configured to determine whether the display panel is in a second temperature condition, and in response to determining that the display panel is in the second temperature condition, adjust the RGB value of the display panel to a predicted second RGB value, wherein the adjustment mode includes: obtaining a plurality of sample first RGB values obtained after a plurality of sample display panels are subjected to gamma adjustment under a first temperature condition and a plurality of sample second RGB values obtained after the plurality of sample display panels are subjected to gamma adjustment under a second temperature condition; the sample first RGB values include a sample first R value, and the sample second RGB values include a sample second R value; performing fitting based on the plurality of sample first RGB values and the plurality of sample second RGB values to obtain a prediction function; the prediction function includes a first prediction function, wherein a linear regression function is constructed based on the sample first R value and the sample second R value, the linear regression function includes a slope parameter and an intercept parameter; a derivative of a goodness of fit of a current linear regression function with respect to a current value of the slope parameter and a current value of the intercept parameter is determined; the current value of the slope parameter and the current value of the intercept parameter are updated based on the derivative and a preset learning rate hyperparameter; a predicted sample second RGB value is obtained by the current linear regression function after the current value of the slope parameter and the current value of the intercept parameter are adjusted, based on the sample first R value; the goodness of fit of the current linear regression function is determined based on the sample second R value and the predicted sample second RGB value, until the goodness of fit of the current linear regression function meets a preset condition, and the current linear regression function is taken as the first prediction function; obtaining a current first RGB value of a target display panel after the target display panel is subjected to gamma adjustment under the first temperature condition, and obtaining a predicted second RGB value by performing prediction on the current first RGB value based on the prediction function; determining whether the target display panel is under the second temperature condition, and adjusting an RGB value of the target display panel to the predicted second RGB value in response to a determination that the target display panel is under the second temperature condition.

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