Temperature drift compensation method of display panel and display device

Abstract

The invention provides a temperature drift compensation method of a display panel and a display device. The method comprises the steps of obtaining a plurality of sample first RGB values obtained after gamma adjustment is performed on a plurality of sample display panels under a first temperature condition and a plurality of sample second RGB values obtained after gamma adjustment is performed on the plurality of sample display panels 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 the target display panel after gamma adjustment under the first temperature condition, and performing prediction based on the current first RGB value through a prediction function to obtain a predicted second RGB value; and judging whether the target display panel is under a second temperature condition or not, 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. According to the invention, the brightness or color coordinate deviation of the target display panel under the influence of the 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 displays, and in particular to a temperature drift compensation method for a display panel and a display device. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the disclosure recited in the claims. No description herein is admitted to be prior art by inclusion in this section.

[0003] Gamma Tuning means that the brightness perceived by the human eye is not in a linear relationship with the actual display brightness of the display panel. In a low-brightness environment, the human eye is more sensitive to changes in brightness, and vice versa in a high-brightness environment. This characteristic of the human eye is called the Gamma characteristic. Due to the nonlinear perception of brightness by the human eye, if a uniformly changing brightness perception is required, the brightness displayed by the display panel needs to change non-uniformly to adapt to the Gamma characteristics of the human eye. The nonlinear parameters of the brightness and grayscale of the display panel can be called Gamma parameters, and the curve drawn according to the Gamma parameters is called the Gamma curve. The Gamma parameters describe the nonlinear relationship between brightness and grayscale, that is, the nonlinear 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 above-mentioned Gamma curve, the display panel needs to be Gamma corrected.

[0004] In the related art, gamma adjustment is usually performed on the display panel under normal temperature conditions. However, the actual use environment of the display device including the display panel may 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 shift, resulting in poor display effect. Summary of the invention

[0005] In view of this, the purpose of the present disclosure is to provide a temperature drift compensation method for a display panel and a display device, which at least solve one of the technical problems in the related art to a certain extent.

[0006] Based on the above purpose, a first aspect of an exemplary embodiment of the present disclosure provides a method for compensating for temperature drift of a display panel, comprising:

[0007] Acquire several sample first RGB values ​​obtained after gamma adjustment of several sample display panels under a first temperature condition and several sample second RGB values ​​obtained after gamma adjustment of several sample display panels under a second temperature condition;

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

[0009] Acquire a current first RGB value of the target display panel after gamma adjustment under the first temperature condition, and perform prediction based on the current first RGB value using the prediction function to obtain a predicted second RGB value;

[0010] It is determined 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, the RGB value of the target display panel is adjusted to the predicted second RGB value.

[0011] In some exemplary embodiments, each of the plurality of sample display panels corresponds to a plurality of brightness values, and each of the brightness values ​​corresponds to a plurality of grayscale binding points;

[0012] Then, the step of obtaining 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 a plurality of sample display panels under a second temperature condition comprises:

[0013] Obtain a sample first R value, a sample first G value, a sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the plurality of sample display panels, and a sample second R value, a sample second G value, a sample second B value among the sample second RGB values;

[0014] Then, performing fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function includes:

[0015] Based on the sample first R value, sample first G value, sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value of each sample display panel among the several sample display panels and the sample second R value, sample second G value, sample second B value among the sample second RGB values, fitting is performed to obtain several prediction functions.

[0016] In some exemplary embodiments, the fitting of the sample first R value, the sample first G value, the sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the several sample display panels and the sample second R value, the sample second G value, the sample second B value among the sample second RGB values ​​to obtain several prediction functions includes:

[0017] Perform fitting based on a number of the first R values ​​of the samples and a number of the second R values ​​of the samples to obtain a first prediction function;

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

[0019] A third prediction function is obtained by performing fitting based on a number of the first B values ​​of the samples and a number of the second B values ​​of the samples.

[0020] In some exemplary embodiments, the fitting based on the plurality of first R values ​​of the samples and the plurality of second R values ​​of the samples to obtain the first prediction function includes:

[0021] Constructing a linear regression function based on the first R value of the sample and the second R value of the sample, wherein the linear regression function includes a slope parameter and an intercept parameter;

[0022] Adjusting the current value of the slope parameter and the current value of the intercept parameter in the linear regression function, and performing prediction based on the first R value of the sample by using the current linear regression function after adjusting the current value of the slope parameter and the current value of the intercept parameter to obtain a predicted second RGB value of the sample;

[0023] Based on the second R value of the sample and the second RGB value of the predicted sample, the goodness of fit of the current linear regression function is determined until the goodness of fit of the current linear regression function meets a preset condition, and the current linear regression function is used as the first prediction function.

[0024] In some exemplary embodiments, adjusting the current value of the slope parameter and the 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 a current value of the slope parameter and a current value of the intercept parameter;

[0026] 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.

[0027] In some exemplary embodiments, 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:

[0028] Determine 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;

[0029] The step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function meets a preset condition comprises:

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

[0031] In some exemplary embodiments, the step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function satisfies a preset condition further includes:

[0032] 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 used as the first prediction function.

[0033] In some exemplary embodiments, after determining whether the target display panel is under the second temperature condition, the method further includes:

[0034] In response to determining that the target display panel is under 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;

[0035] The RGB value of the target display panel is adjusted to the predicted third RGB value.

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

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

[0038] Display panel and gamma adjustment device;

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

[0040] From the above, it can be seen that the temperature drift compensation method and display device of the display panel provided by the embodiment of the present disclosure include: obtaining several sample first RGB values ​​obtained after gamma adjustment of several sample display panels under the first temperature condition and several sample second RGB values ​​obtained after gamma adjustment under the second temperature condition; fitting based on the several sample first RGB values ​​and the several sample second RGB values ​​to obtain a prediction function; obtaining the current first RGB value of the target display panel after gamma adjustment under the first temperature condition, predicting based on the current first RGB value through the prediction function to obtain a predicted second RGB value; judging 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 THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings required for use in the embodiments or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic flow chart of a method for compensating for temperature drift of a display panel provided by an exemplary embodiment of the present disclosure;

[0043] Figure 2 A schematic diagram of a fitting method provided for an exemplary embodiment of the present disclosure;

[0044] Figure 3 Another schematic diagram of a fitting method provided for an exemplary embodiment of the present disclosure;

[0045] Figure 4 A schematic diagram of a gamma curve provided for an exemplary embodiment of the present disclosure without applying the solution of the present disclosure;

[0046] Figure 5 A schematic diagram of a gamma curve to which the solution of the present disclosure is applied is provided for an exemplary embodiment of the present disclosure;

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

[0048] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, the principles and spirit of the present disclosure will be described with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present disclosure, and are not intended to limit the scope of the present disclosure in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] It should be understood herein that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction rather than having 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 by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. The article "one" or "a" before an element does not exclude the existence of multiple such elements.

[0051] The principle and spirit of the present disclosure are explained in detail below with reference to several representative embodiments of the present disclosure.

[0052] Gamma Tuning means that the brightness perceived by the human eye is not in a linear relationship with the actual display brightness of the display panel. In a low-brightness environment, the human eye is more sensitive to changes in brightness, and vice versa in a high-brightness environment. This characteristic of the human eye is called the Gamma characteristic. Due to the nonlinear perception of brightness by the human eye, if a uniformly changing brightness perception is required, the brightness displayed by the display panel needs to change non-uniformly to adapt to the Gamma characteristics of the human eye. The nonlinear parameters of the brightness and grayscale of the display panel can be called Gamma parameters, and the curve drawn according to the Gamma parameters is called the Gamma curve. The Gamma parameters describe the nonlinear relationship between brightness and grayscale, that is, the nonlinear 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 above-mentioned Gamma curve, the display panel needs to be Gamma corrected.

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

[0054] In order to solve the above problems, the present disclosure provides a temperature drift compensation solution for a display panel, which specifically includes: obtaining a number of sample first RGB values ​​obtained after gamma adjustment of a number of sample display panels under a first temperature condition and a number of sample second RGB values ​​obtained after gamma adjustment under a second temperature condition; fitting based on the number of sample first RGB values ​​and the number of sample second RGB values ​​to obtain a prediction function; obtaining a current first RGB value of a target display panel after gamma adjustment under the first temperature condition, and predicting based on the current first RGB value through the prediction function to obtain a predicted second RGB value; judging 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 the specific implementation, the RGB value of the sample display panel under normal temperature and the RGB value under high temperature (or low temperature, high temperature is used for explanation here, and the same applies to low temperature) are fitted to obtain a prediction function between the RGB value under normal temperature and the RGB value under high temperature. Then, the prediction function is written into the gamma adjustment device corresponding to the target display panel, and after the target display panel is gamma-adjusted under normal temperature, the RGB value of the target display panel under normal temperature is obtained. The RGB value under high temperature is calculated based on the RGB value under normal temperature and the prediction function, and the RGB value under high temperature is stored in the gamma adjustment device corresponding to the target display panel. Finally, in the actual use of the display device including the target display panel, when the target display panel is under high temperature, the RGB value of the target display panel is adjusted to the RGB value under high temperature stored in the gamma adjustment device corresponding to the target display panel. The RGB value is used to affect the brightness or color coordinates. Specifically, the brightness can be calculated by weighted summation of the RGB values; the RGB value can be converted into the color coordinates by the conversion formula, thereby compensating for the brightness or color coordinate offset of the target display panel when it is affected by temperature, and improving 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 are specifically described below. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principles of the present disclosure, and the embodiments of the present disclosure are not limited in this regard. On the contrary, the embodiments of the present disclosure can be applied to any applicable scenario.

[0057] refer to Figure 1 , which is a flow chart of a method for compensating for temperature drift of a display panel provided by an exemplary embodiment of the present disclosure.

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

[0059] Step S110 , obtaining 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 a plurality of sample display panels under a second temperature condition.

[0060] In some exemplary embodiments, several sample display panels are produced based on the same process conditions.

[0061] During specific implementation, several display panels produced in the same batch are selected as sample display panels.

[0062] Among them, taking into account that compared with the display panels generated under the same process conditions, there may be large differences between the display panels generated under different process conditions, so that the accuracy of the prediction function obtained by fitting the data of the display panels generated under different process conditions is low, and then the accuracy of the gamma adjustment of the display panels is low. Therefore, in the specific implementation, several display panels produced based on the same process conditions are selected as sample display panels, and further, several display panels produced in the same batch are selected as sample display panels, which improves the accuracy of the prediction function obtained by fitting and improves the accuracy of the gamma adjustment of the display panels.

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

[0064] The greater the number of sample display panels, the higher the accuracy of the fitted prediction function, and the higher the accuracy of the gamma adjustment for the display panel.

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

[0066] Among them, considering that if the production process conditions of the sample display panel used to obtain the prediction function and the target display panel to which the prediction function is applied are different, the prediction function obtained based on the sample display panel may not be suitable for the target display panel, and thus the accuracy of gamma adjustment of the display panel is low. Therefore, in a specific implementation, the production process conditions of the sample display panel used to obtain the prediction function and the target display panel to which the prediction function is applied are the same, thereby improving the accuracy of gamma adjustment of the target display panel.

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

[0068] As an example, normal temperature conditions include 20°C to 25°C;

[0069] High temperature conditions include 40°C to 50°C;

[0070] Low temperature conditions include 0°C to -10°C.

[0071] In some exemplary embodiments, each of the plurality of sample display panels corresponds to a plurality of brightness values, and each of the brightness values ​​corresponds to a plurality of grayscale binding points;

[0072] Then, the step of obtaining 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 a plurality of sample display panels under a second temperature condition comprises:

[0073] Obtain a sample first R value, a sample first G value, a sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the several sample display panels, and a sample second R value, a sample second G value, a sample second B value among the sample second RGB values.

[0074] In a specific implementation, the method of obtaining 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 a plurality of sample display panels under a second temperature condition comprises the following steps:

[0075] Step S210: performing gamma adjustment on the plurality of sample display panels under the first temperature condition to obtain a sample first RGB value of each sample display panel among the plurality of sample display panels.

[0076] In a specific implementation, the first temperature condition includes a normal temperature condition, for example, a temperature between 20°C and 25°C.

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

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

[0079] In a specific implementation, the display panel has a number of brightnesses, each brightness corresponds to a number of binding points, and the sample first RGB value includes an R value, a G value, and a B value of each binding point at each brightness.

[0080] Step S220: performing gamma adjustment on the plurality of sample display panels under the second temperature condition to obtain a sample second RGB value of each sample display panel among the plurality of sample display panels.

[0081] In a specific implementation, the second temperature condition includes a high temperature condition, for example, a temperature between 40°C and 50°C, and the second temperature condition includes a low temperature condition, for example, a temperature between 0°C and -10°C.

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

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

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

[0085] In a specific implementation, the display panel has a number of brightnesses, each brightness corresponds to a number of binding points, and the sample second RGB value includes an R value, a G value, and a B value of each binding point at each brightness.

[0086] Step S120: performing fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function.

[0087] In some exemplary embodiments, each of the plurality of sample display panels corresponds to a plurality of brightness values, and each of the brightness values ​​corresponds to a plurality of grayscale binding points;

[0088] Then, performing fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function includes:

[0089] Based on the sample first R value, sample first G value, sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value of each sample display panel among the several sample display panels and the sample second R value, sample second G value, sample second B value among the sample second RGB values, fitting is performed to obtain several prediction functions.

[0090] In some exemplary embodiments, the fitting of the sample first R value, the sample first G value, the sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the several sample display panels and the sample second R value, the sample second G value, the sample second B value among the sample second RGB values ​​to obtain several prediction functions includes:

[0091] Perform fitting based on a number of the first R values ​​of the samples and a number of the second R values ​​of the samples to obtain a first prediction function;

[0092] Perform fitting based on a number of the first G values ​​of the samples and a number of the second G values ​​of the samples to obtain a second prediction function;

[0093] A third prediction function is obtained by performing fitting based on a number of the first B values ​​of the samples and a number of the second B values ​​of the samples.

[0094] When implementing it, refer to Figure 2 , which is based on one channel (R value, G value or B value) in RGB to obtain a visual representation of the fitting result.

[0095] When implementing it, refer to Figure 3 The display panel has several brightnesses, each brightness corresponds to several binding points, and each color channel (R value, G value or B value) in the RGB value of each binding point at each brightness is fitted separately to obtain a prediction function.

[0096] In some exemplary embodiments, the fitting based on the plurality of first R values ​​of the samples and the plurality of second R values ​​of the samples to obtain the first prediction function includes:

[0097] Constructing a linear regression function based on the first R value of the sample and the second R value of the sample, wherein the linear regression function includes a slope parameter and an intercept parameter;

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

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

[0100] In some exemplary embodiments, 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 a current value of the slope parameter and a current value of the intercept parameter;

[0102] 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.

[0103] In some exemplary embodiments, 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:

[0104] Determine 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;

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

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

[0107] In some exemplary embodiments, the step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function satisfies a preset condition further includes:

[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, the current linear regression function is used as the first prediction function.

[0109] In the specific implementation, the linear regression fitting method is taken as an example for explanation, and the prediction function is constructed as follows:

[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 + offset value = second temperature REGG;

[0113] In specific implementation, when the first temperature is room 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] Among them, REGR represents the R value in the register, REG represents the register. The register is a small high-speed storage device used to store and process data. It is usually directly connected to the CPU and is used to store temporary data, addresses, and control information. 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 set to 0, and the increase or decrease amount of each fitting is ±0.001 (adjusted according to actual conditions). After each fitting is completed, the loss (Loss) is obtained by calculating the variance between the predicted second RGB value of each prediction function, that is, the predicted value and the sample second RGB value, that is, the actual value. 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 fitting results, the above loss function is established. In linear regression, the loss function is the variance between the function prediction value and the actual value (the loss function under linear regression has a clear minimum point to prevent the linear regression function from falling 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 is the global optimal solution for the collected data. By establishing a loss function, it can be ensured that the obtained prediction function is the optimal solution for the current data 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 it is necessary to collect data again or adjust the fitting parameters.

[0120] In specific implementation, a gradient descent algorithm can be used during fitting to increase the fitting speed, especially when the amount of data is large, which can save fitting time.

[0121] Among them, the gradient descent algorithm is a kind of iterative method, which can be used to solve the least squares problem (applicable to both linear and nonlinear) to solve the model parameters of the machine learning algorithm, that is, unconstrained optimization problem.

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

[0123] Step S130: obtaining a current first RGB value of the target display panel after gamma adjustment under the first temperature condition, and performing prediction based on the current first RGB value by using the prediction function to obtain a predicted second RGB value.

[0124] During specific implementation, the fitted prediction function 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 is used to store temporary data, addresses and control information, etc.

[0126] Step S140: determining 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, adjusting the RGB value of the target display panel to the predicted second RGB value.

[0127] In a specific implementation, during the actual use of a display device including a 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 a gamma adjustment device corresponding to the target display panel, thereby compensating for the brightness or color coordinate deviation of the target display panel when affected by temperature, and improving 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 a temperature between 20°C and 25°C, and the second temperature condition includes a high temperature condition or a low temperature condition, such as a temperature between 40°C and 50°C or a temperature between 0°C and -10°C. However, the present disclosure is not limited thereto. In addition to being applicable to one target temperature, the present disclosure can also be applied to multiple target temperatures, including at least the following two methods:

[0129] As an example, if the display device including the target display panel is actually used under two temperature conditions of 40°C and 0°C, the predicted RGB value is determined based on 40°C and 0°C, respectively, and stored in the gamma adjustment device corresponding to the target display panel. When it is at the corresponding temperature, the predicted RGB value is called.

[0130] As an example, if the first temperature is 20° C. and the second temperature is 40° C., and the display device including the target display panel is actually in use at a temperature between 20° C. and 40° C., then:

[0131] In response to determining that the target display panel is under 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;

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

[0133] refer to Figure 4 , which is a gamma curve of a display panel in the related art, that is, a gamma curve to which the solution of the present disclosure is not applied; Figure 5 , which is a gamma curve to which the solution of the present disclosure is applied.

[0134] The ideal Gamma curve should be a straight line, but in reality, due to the physical limitations of display devices, the curve is often nonlinear. Although there is no unified standard for the Gamma value of displays, most displays use 2.2 as the recommended Gamma value.

[0135] like Figure 4 As shown in FIG. 1 , the gamma curve without the solution of the present disclosure, especially when the grayscale value is low, deviates far from 2.2. Figure 5 As shown, the gamma curve to which the solution of the present disclosure is applied has a gamma parameter of about 2.2, which is 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 embodiment of the present disclosure includes: obtaining a number of sample first RGB values ​​obtained after gamma adjustment of a number of sample display panels under a first temperature condition and a number of sample second RGB values ​​obtained after gamma adjustment under a second temperature condition; fitting based on the number of sample first RGB values ​​and the number of sample second RGB values ​​to obtain a prediction function; obtaining a current first RGB value of a target display panel after gamma adjustment under the first temperature condition, predicting based on the current first RGB value through the prediction function to obtain a predicted second RGB value; judging 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.

[0137] Through the present disclosure, RGB values ​​are used to affect brightness or color coordinates. Specifically, brightness can be calculated by weighted summation of RGB values; RGB values ​​can be converted into color coordinates through a conversion formula, compensating for the brightness or color coordinate offset of the target display panel when affected by temperature, thereby improving the display effect of the target display panel.

[0138] By collecting the Gamma register value of the target temperature and calculating a Gamma curve for the target temperature alone instead of biasing the voltage of the light-emitting material in the related art, the compensation effect is significant.

[0139] The collected Gamma data is processed by using a linear regression algorithm in conjunction with a loss function, which avoids the low accuracy and difficulty in quantifying the accuracy when manually determining the compensation coefficient in related technologies. 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. It also performs well when the amount of data is large. The big data model makes the fitting result more effective on batch products and greatly improves the accuracy of compensation.

[0140] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described 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 actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

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

[0143] The display device comprises:

[0144] Display panel and gamma adjustment device;

[0145] The gamma adjustment device is configured to determine whether the display panel is under a second temperature condition, and in response to determining that the display panel is under 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 by dividing it into various modules according to its functions. Of course, when implementing 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 embodiment is used to implement the corresponding display panel temperature drift compensation method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0148] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the temperature drift compensation method for the display panel described in any of the above embodiments is implemented.

[0149] Figure 6 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may 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 in the device.

[0150] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0151] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this 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 used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

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

[0154] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[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 may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

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

[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 via the bus 1030, so that the processor 1010 executes the following instructions when running:

[0158] Acquire several sample first RGB values ​​obtained after gamma adjustment of several sample display panels under a first temperature condition and several sample second RGB values ​​obtained after gamma adjustment of several sample display panels under a second temperature condition;

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

[0160] Acquire a current first RGB value of the target display panel after gamma adjustment under the first temperature condition, and perform prediction based on the current first RGB value using the prediction function to obtain a predicted second RGB value;

[0161] It is determined 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, the RGB value of the target display panel is adjusted to the predicted second RGB value.

[0162] In a possible implementation, in the instruction executed by the processor 1010, each sample display panel in the plurality of sample display panels corresponds to a plurality of brightness values, and each of the brightness values ​​corresponds to a plurality of grayscale binding points;

[0163] Then, the step of obtaining 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 a plurality of sample display panels under a second temperature condition comprises:

[0164] Obtain a sample first R value, a sample first G value, a sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the plurality of sample display panels, and a sample second R value, a sample second G value, a sample second B value among the sample second RGB values;

[0165] Then, performing fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function includes:

[0166] Based on the sample first R value, sample first G value, sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value of each sample display panel among the several sample display panels and the sample second R value, sample second G value, sample second B value among the sample second RGB values, fitting is performed to obtain several prediction functions.

[0167] In a possible implementation manner, in the instructions executed by the processor 1010, the sample first R value, the sample first G value, the sample first B value of the sample first RGB value corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel in the plurality of sample display panels and the sample second R value, the sample second G value, the sample second B value of the sample second RGB value are fitted to obtain several prediction functions, including:

[0168] Perform fitting based on a number of the first R values ​​of the samples and a number of the second R values ​​of the samples to obtain a first prediction function;

[0169] Perform fitting based on a number of the first G values ​​of the samples and a number of the second G values ​​of the samples to obtain a second prediction function;

[0170] A third prediction function is obtained by performing fitting based on a number of the first B values ​​of the samples and a number of the second B values ​​of the samples.

[0171] In a possible implementation manner, in the instructions executed by the processor 1010, the fitting based on the plurality of first R values ​​of the samples and the plurality of second R values ​​of the samples to obtain the first prediction function includes:

[0172] Constructing a linear regression function based on the first R value of the sample and the second R value of the sample, wherein the linear regression function includes a slope parameter and an intercept parameter;

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

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

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

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

[0177] 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.

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

[0179] Determine 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;

[0180] The step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function meets a preset condition comprises:

[0181] Until the variance of the sample second R value and the predicted sample second RGB value is minimized, the current linear regression function is used as the first prediction function.

[0182] In a possible implementation manner, in the instructions executed by the processor 1010, the step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function satisfies a preset condition further includes:

[0183] 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 used as the first prediction function.

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

[0185] In response to determining that the target display panel is under 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] The RGB value of the target display panel is adjusted to the predicted third RGB value.

[0187] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the temperature drift compensation method of the display panel as described in any of the above embodiments.

[0188] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. Information can be a computer-readable instruction, a data structure, a module of a program, 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 technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassette, magnetic tape magnetic disk storage or other magnetic storage device or any other non-transmission medium, which can be used to store information that can be accessed 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 disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)), etc.

[0190] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the temperature drift compensation method of the display panel described in any embodiment in the above exemplary method part, and have the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0191] Based on the same inventive concept, corresponding to the temperature drift compensation method of the display panel described in any of the above embodiments, the present disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer so that the computer and / or the processor execute the temperature drift compensation method of the display panel. Corresponding to the execution subject corresponding to each step in each embodiment of the temperature drift compensation method of the display panel, the processor that executes the corresponding step may belong to the corresponding execution subject.

[0192] The computer program product of the above embodiment is used to enable the computer and / or the processor to 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 will not be repeated here.

[0193] Those skilled in the art will appreciate that the embodiments of the present disclosure may be implemented as a system, method, or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." In addition, in some embodiments, the present disclosure may also be implemented in the form of a computer program product in one or more computer-readable media, which contains computer-readable program code.

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

[0195] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0196] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0197] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0198] It should be understood that each box in the flow chart and / or block diagram and the combination of boxes in the flow chart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified in the boxes in the flow chart and / or block diagram.

[0199] These computer program instructions may also be stored in a computer-readable medium that enables a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable medium produce a product that includes an instruction device that implements the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0200] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable device to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0201] In addition, although the operations of the disclosed method are described in a specific order in the accompanying drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. On the contrary, the steps depicted in the flow chart can change the order of execution. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution.

[0202] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0203] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0204] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0205] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the following fact, that is, the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuit) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0206] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0207] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

[0208] Although the spirit and principle of the present disclosure have been described with reference to several specific embodiments, it should be understood that the present disclosure is not limited to the disclosed specific embodiments, and the division of various aspects does not mean that the features in these aspects cannot be combined to benefit, and such division is only for the convenience of expression. The present disclosure is intended to cover various modifications and equivalent arrangements included in the spirit and scope of the attached claims. The scope of the attached claims conforms to the broadest interpretation, thereby including all such modifications and equivalent structures and functions.

Claims

1. A method for compensating temperature drift of a display panel, characterized in that: include: Acquire several sample first RGB values ​​obtained after gamma adjustment of several sample display panels under a first temperature condition and several sample second RGB values ​​obtained after gamma adjustment of several sample display panels under a second temperature condition; Perform fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function; Acquire a current first RGB value of the target display panel after gamma adjustment under the first temperature condition, and perform prediction based on the current first RGB value using the prediction function to obtain a predicted second RGB value; It is determined 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, the RGB value of the target display panel is adjusted to the predicted second RGB value.

2. The method according to claim 1, characterized in that Each sample display panel of the plurality of sample display panels corresponds to a plurality of brightness values, and each of the brightness values ​​corresponds to a plurality of grayscale binding points; Then, the step of obtaining 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 a plurality of sample display panels under a second temperature condition comprises: Obtain a sample first R value, a sample first G value, a sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the plurality of sample display panels, and a sample second R value, a sample second G value, a sample second B value among the sample second RGB values; Then, performing fitting based on the first RGB values ​​of the plurality of samples and the second RGB values ​​of the plurality of samples to obtain a prediction function includes: Based on the sample first R value, sample first G value, sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value of each sample display panel among the several sample display panels and the sample second R value, sample second G value, sample second B value among the sample second RGB values, fitting is performed to obtain several prediction functions.

3. The method according to claim 2, characterized in that The fitting of the sample first R value, the sample first G value, the sample first B value among the sample first RGB values ​​corresponding to each grayscale binding point corresponding to each brightness value corresponding to each sample display panel among the several sample display panels and the sample second R value, the sample second G value, the sample second B value among the sample second RGB values ​​to obtain several prediction functions includes: Perform fitting based on a number of the first R values ​​of the samples and a number of the second R values ​​of the samples to obtain a first prediction function; Perform fitting based on a number of the first G values ​​of the samples and a number of the second G values ​​of the samples to obtain a second prediction function; A third prediction function is obtained by performing fitting based on a number of the first B values ​​of the samples and a number of the second B values ​​of the samples.

4. The method according to claim 3, characterized in that 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 includes: Constructing a linear regression function based on the first R value of the sample and the second R value of the sample, wherein the linear regression function includes a slope parameter and an intercept parameter; Adjusting the current value of the slope parameter and the current value of the intercept parameter in the linear regression function, and performing prediction based on the first R value of the sample by using the current linear regression function after adjusting the current value of the slope parameter and the current value of the intercept parameter to obtain a predicted second RGB value of the sample; Based on the second R value of the sample and the second RGB value of the predicted sample, the goodness of fit of the current linear regression function is determined until the goodness of fit of the current linear regression function meets a preset condition, and the current linear regression function is used as the first prediction function.

5. The method according to claim 4, characterized in that The adjusting the current value of the slope parameter and the current value of the intercept parameter in the linear regression function comprises: determining a derivative of the goodness of fit of the current linear regression function with respect to a current value of the slope parameter and a current value of the intercept parameter; 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.

6. The method according to claim 4, characterized in that 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: Determine 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 step of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function meets a preset condition comprises: Until the variance of the sample second R value and the predicted sample second RGB value is minimized, the current linear regression function is used as the first prediction function.

7. The method according to claim 6, characterized in that The method of using the current linear regression function as the first prediction function until the goodness of fit of the current linear regression function meets a preset condition 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 used as the first prediction function.

8. The method according to claim 1, characterized in that After determining whether the target display panel is under the second temperature condition, the method further includes: In response to determining that the target display panel is under 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; The RGB value of the target display panel is adjusted to the predicted third RGB value.

9. The method according to claim 1, characterized in that: The plurality of sample display panels and the target display panel are produced based on the same process conditions.

10. A display device, characterized in that: include: Display panel and gamma adjustment device; The gamma adjustment device is configured to determine whether the display panel is under a second temperature condition, and in response to determining that the display panel is under the second temperature condition, adjust the RGB value of the display panel to a predicted second RGB value.

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