Display driving method, display driving device and display panel

Abstract

The present disclosure provides a display driving method, which is applied to the technical field of display. The method comprises: obtaining panel temperature and luminance data of a display panel for a target gray scale; determining a target luminance for the target gray scale according to a preset mapping relationship and the panel temperature, wherein the preset mapping relationship represents a mapping relationship between the luminance data, the gray scale and the panel temperature for the display panel; and driving the display panel to display according to driving data determined based on the target luminance and the luminance data. The present disclosure also provides a display driving device, a display panel, an electronic device, a medium and a program product.

Description

Technical Field

[0001] This disclosure relates to the field of display technology, and more specifically, to a display driving method, display driving device, display panel, electronic device, medium, and program product. Background Technology

[0002] With the continuous development of organic light-emitting diode (OLED) technology, higher requirements are being placed on OLED products in terms of display bezels, refresh rates, power consumption, and image quality. All-oxide backplane driving technology can meet these requirements. However, in display scenarios with sustained high brightness and high grayscale, OLED panels with all-oxide backplane driving experience a rapid temperature rise during display, causing the panel's brightness to increase with temperature. This results in abnormal display effects and negatively impacts the user's visual experience. Summary of the Invention

[0003] In view of the above, one aspect of this disclosure provides a display driving method, comprising:

[0004] Obtain the panel temperature and brightness data of the display panel for the target grayscale;

[0005] Based on a preset mapping relationship and panel temperature, the target brightness for the target grayscale is determined. The preset mapping relationship represents the mapping relationship between brightness data, grayscale, and panel temperature for the display panel.

[0006] The display panel is driven to display based on the driving data determined by the target brightness and brightness data.

[0007] According to embodiments of this disclosure, the preset mapping relationship is determined using the following operations:

[0008] An initial mapping relationship is created based on sample datasets for multiple preset gray levels. Each sample dataset includes sample panel temperature and sample brightness data for the preset gray levels. The initial mapping relationship represents the mapping relationship between sample brightness data, preset gray levels, and sample panel temperature.

[0009] Based on the grayscale compensation value and temperature compensation value for each preset grayscale, the preset grayscale and sample panel temperature of the initial mapping relationship are corrected respectively to obtain the preset mapping relationship. The grayscale compensation value is obtained by processing the preset grayscale using the grayscale compensation function, and the temperature compensation value is obtained by processing the sample panel temperature using the temperature compensation function.

[0010] According to an embodiment of this disclosure, the grayscale compensation function is created based on a first polynomial, and the grayscale compensation function represents the mapping relationship between a preset grayscale and a grayscale compensation value.

[0011] According to embodiments of this disclosure, the temperature compensation function is created based on a second polynomial, and the temperature compensation function characterizes the mapping relationship between the sample panel temperature and the temperature compensation value.

[0012] According to embodiments of this disclosure, the sample dataset is determined using the following operations:

[0013] Obtain an initial sample dataset for multiple preset gray levels, wherein each sample data in the initial sample dataset includes sample panel temperature and sample brightness data for each preset gray level;

[0014] The initial sample dataset is augmented using a sample augmentation model to obtain a new sample dataset. The sample augmentation model is obtained by training a neural network using the initial sample dataset.

[0015] According to embodiments of this disclosure, training a neural network using an initial sample dataset includes:

[0016] The preset grayscale and sample panel temperature in the sample data are input into the neural network to output the predicted brightness.

[0017] Based on the difference between the predicted brightness and the sample brightness data, the parameters of the neural network are adjusted until the difference converges.

[0018] According to embodiments of this disclosure, the initial sample dataset is augmented using a sample augmentation model to obtain a sample dataset comprising:

[0019] Input the preset enhanced grayscale and enhanced temperature into the sample enhancement model, and output enhanced brightness;

[0020] Enhanced grayscale, enhanced temperature, and enhanced brightness are added to the initial sample dataset to obtain the sample dataset.

[0021] According to embodiments of this disclosure, the brightness data includes the brightness value of each pixel, or the brightness data includes the display brightness value of the display panel;

[0022] Based on the driving data determined according to the target brightness and brightness data, the driving display panel displays the following:

[0023] Based on the target brightness and the brightness value of each pixel, determine the driving data of the display panel for the target grayscale, or based on the target brightness and the display brightness value, determine the driving data of the display panel for the target grayscale, wherein the driving data includes the compensation voltage value of each pixel in the display panel;

[0024] The display panel is driven using driving data. Another aspect of this disclosure provides a display driving device, comprising:

[0025] The first acquisition module is used to acquire the panel temperature and brightness data of the display panel for the target grayscale.

[0026] The determination module is used to determine the target brightness for a target grayscale based on a preset mapping relationship and panel temperature. The preset mapping relationship represents the mapping relationship between brightness data, grayscale, and panel temperature for the display panel.

[0027] The driving module is used to drive the display panel to display based on driving data determined based on the target brightness and brightness data.

[0028] Another aspect of this disclosure provides a display panel including the aforementioned display driving device.

[0029] Another aspect of this disclosure provides an electronic device comprising:

[0030] One or more processors;

[0031] Memory, used to store one or more programs.

[0032] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described method.

[0033] Another aspect of this disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed, are used to implement the method described above.

[0034] Another aspect of this disclosure provides a computer program product including computer-executable instructions that, when executed, are used to implement the method described above.

[0035] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0036] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0037] Figure 1 This is a flowchart of a display driving method according to an embodiment of the present disclosure;

[0038] Figure 2A This is a schematic diagram of a display driving method according to an embodiment of the present disclosure;

[0039] Figure 2BThis is a schematic diagram of a display driving method according to another embodiment of the present disclosure;

[0040] Figure 3 This is a schematic diagram illustrating the determination of a preset mapping relationship according to an embodiment of this disclosure;

[0041] Figure 4 This is a schematic diagram illustrating the determination of a sample dataset according to an embodiment of this disclosure;

[0042] Figure 5 This is a schematic diagram illustrating the determination of hyperparameters according to an embodiment of this disclosure;

[0043] Figure 6 This is a block diagram of a display driving device according to an embodiment of the present disclosure;

[0044] Figure 7 This is a block diagram of an apparatus for generating a preset mapping relationship according to an embodiment of the present disclosure;

[0045] Figure 8 This is a schematic diagram of a display panel according to an embodiment of the present disclosure; and

[0046] Figure 9 This is a block diagram of an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure. Detailed Implementation

[0047] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0048] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0049] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0050] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0051] As a next-generation display device, OLED's applications in displays, lighting, and computers continue to expand. With ongoing research into technologies and integration processes for large-size displays, higher demands will be placed on OLED products regarding display bezels, refresh rates, power consumption, and image quality. In this example, the OLED display backplane driving circuit primarily employs Low Temperature Poly-silicon (LTPS) and Low Temperature Polycrystalline Oxide (LTPO) backplane driving technologies. Due to the high power consumption and large leakage current of LTPS, and the limitations of LTPO in areas such as flicker and VRR, it is difficult to meet the aforementioned requirements.

[0052] All-oxide backplane driving technology can meet the above requirements. However, in display scenarios with continuous high brightness and high grayscale, the temperature of OLED panels with all-oxide backplane driving rises rapidly during display, causing the panel brightness to rise with the temperature, which in turn leads to abnormal display effects and affects the user's visual experience.

[0053] To address the aforementioned technical problems, embodiments of this disclosure provide a display driving method. This method utilizes the mapping relationship between brightness data, grayscale, and panel temperature to determine the target brightness corresponding to each grayscale level, and then drives the display panel to display based on the target brightness. By introducing a temperature parameter into this mapping relationship and using it to drive the display panel, the problem of abnormal light emission caused by temperature rise is solved, allowing the display panel to approach the target light emission brightness.

[0054] Figure 1 This is a flowchart of a display driving method according to an embodiment of the present disclosure.

[0055] like Figure 1 As shown, the display driving method of this embodiment includes operations S110 to S130.

[0056] In operation S110, the panel temperature and brightness data of the display panel for the target grayscale are obtained.

[0057] The target grayscale can be any grayscale level in the display panel. For example, when the display panel includes grayscale levels from 0 to 255, the target grayscale can be any grayscale level from 0 to 255.

[0058] The panel temperature is the actual temperature of the display panel for the target grayscale, which can be obtained through temperature sensors. For example, M rows × N columns of temperature sensors can be set on the display panel, where M and N are positive integers. Multiple temperature values ​​collected by the M rows × N columns of temperature sensors are obtained, and the average of these multiple temperature values ​​is taken to obtain the panel temperature.

[0059] Brightness data can include the display brightness value of the display panel, which can be the average brightness value of each pixel in the display panel for a target grayscale. Brightness data can also include the brightness value of each pixel in the display panel for the target grayscale. The manufacturing process of the display panel includes a testing process. When testing the display panel, it is necessary to perform spot testing on the display panel at a specific grayscale and obtain the brightness of the display panel at that specific grayscale to analyze the performance of the display panel. Therefore, in some embodiments, the brightness of the display panel at a specific grayscale can be obtained as the brightness data of the display panel at the target grayscale. In other embodiments, brightness data can be obtained by taking pictures of the display panel using a device such as a CCD (charge-coupled device) to collect the brightness of each pixel and obtain the brightness value of each pixel in the display panel for the target grayscale. Alternatively, the average brightness of each collected pixel can be taken to obtain the display brightness value of the display panel.

[0060] For example, if the target grayscale is 100, obtaining the panel temperature and brightness data of the display panel for the target grayscale can include: adjusting the grayscale value of each pixel of the display panel to 100 and then lighting up the display panel, then taking a picture of the display panel with a CCD or other device to obtain the brightness of each pixel, and then the brightness value of each pixel can be used as the brightness data, or the brightness values ​​of each pixel can be averaged to obtain the display brightness value of the display panel, and this display brightness value can be used as the brightness data.

[0061] It should be noted that panel temperature and brightness data corresponding to different gray levels can be collected by adjusting the gray level value of the target gray level.

[0062] In operation S120, the target brightness for the target grayscale is determined based on the preset mapping relationship and panel temperature.

[0063] The preset mapping relationship represents the mapping relationship between brightness data, grayscale, and panel temperature for a display panel. The preset mapping relationship can include multiple mapping arrays, each of which includes brightness value, grayscale, and panel temperature.

[0064] For example, the preset mapping relationship can be shown in Table 1.

[0065] Table 1

[0066] grayscale Panel temperature (°C) Brightness (lm) G1 T1 L1 G2 T2 L2 G2 T3 L3 G3 T4 L4 …… …… …… Gn Tn Ln

[0067] As shown in Table 1, the preset mapping relationship includes n mapping arrays, each mapping array including a grayscale, a panel temperature, and a brightness. For example, the first mapping array includes grayscale G1, panel temperature T1, and brightness L1.

[0068] Determining the target brightness for a target grayscale based on a preset mapping relationship and panel temperature may include: determining the mapping data corresponding to the target grayscale and panel temperature from multiple mapping arrays of the preset mapping relationship, and determining the brightness value in the mapping array as the target brightness. For example, if the target grayscale is G2 and the panel temperature is T3, then the target brightness corresponding to the target grayscale G2 at panel temperature T3 is L3.

[0069] In operation S130, the display panel is driven to display based on the driving data determined based on the target brightness and brightness data.

[0070] According to embodiments of this disclosure, the brightness data includes the brightness value of each pixel; driving the display panel to display based on the target brightness and the brightness data includes: determining the driving data of the display panel for the target grayscale based on the target brightness and the brightness value of each pixel, wherein the driving data includes the compensation voltage value of each pixel in the display panel; and driving the display panel to display using the driving data.

[0071] Determining the driving data for the display panel for the target grayscale based on the target brightness and the brightness value of each pixel may include: determining the compensation brightness value for each pixel based on the target brightness and the brightness value of each pixel, and determining the compensation voltage value for each pixel based on the compensation brightness value.

[0072] According to embodiments of this disclosure, the brightness data may further include the display brightness value of the display panel; driving the display panel to display based on the target brightness and the brightness data includes: determining the driving data of the display panel for a target grayscale based on the target brightness and the display brightness value, wherein the driving data includes the compensation voltage value of each pixel in the display panel; and driving the display panel to display using the driving data.

[0073] Determining the driving data for the display panel for the target grayscale based on the target brightness and the display brightness value may include: determining the compensation brightness value for each pixel based on the target brightness and the display brightness value, and determining the compensation voltage value for each pixel based on the compensation brightness value.

[0074] Driving the display panel using driving data can include: adjusting the voltage value for each pixel according to the compensation voltage value, thereby adjusting each pixel to achieve the target brightness. For example, if the voltage for the i-th pixel is Vi, and the compensation brightness value is ΔL, and the voltage change ΔV for the i-th pixel is determined based on ΔL, then adjusting the voltage of the i-th pixel to Vi + ΔV and driving the i-th pixel to display will achieve the target brightness.

[0075] For example, the driving data can be burned into the memory of the display panel, so that the display panel can adjust the driving voltage using the driving data when displaying, so that the brightness of the display panel is close to the target brightness.

[0076] It should be noted that different gray levels correspond to different driving data. The target gray level in the above method can include all gray levels of the display panel; in this case, the driving data includes the driving data for all gray levels of the display panel. Alternatively, the target gray level can include only a portion of the gray levels of the display panel; in this case, the driving data includes the driving data for only a portion of the gray levels of the display panel.

[0077] By utilizing a preset mapping relationship between the display panel's brightness data, grayscale, and panel temperature, the target brightness corresponding to the target grayscale is determined, and the display panel is driven to display based on the target brightness and brightness data. By introducing a temperature parameter into the preset mapping relationship and using this preset mapping relationship to control the display panel, the problem of abnormal light emission caused by temperature rise is solved, making the display panel closer to the target light emission brightness, which helps to improve the user's visual experience.

[0078] Figure 2A This is a schematic diagram of a display driving method according to an embodiment of the present disclosure.

[0079] like Figure 2A As shown, for display panel 210A, brightness data 230A and panel temperature 240A at target grayscale 220A are obtained. Brightness data 230A includes the brightness value of each pixel, such as brightness value 1, brightness value 2, ..., brightness value n. Then, the target brightness 250A corresponding to the target grayscale 220A and panel temperature 240A is found from the preset mapping relationship. Then, based on the target brightness 250A and the brightness values ​​1, 2, ..., and n in brightness data 230A, the compensation brightness value corresponding to each pixel is determined, and driving data 260A is obtained based on the compensation brightness value. For example, driving data 260A may include compensation voltage value 1, compensation voltage value 2, ..., compensation voltage value n. After that, the display panel is driven to display 270 using driving data 260A.

[0080] Figure 2B This is a schematic diagram of a display driving method according to another embodiment of the present disclosure.

[0081] like Figure 2B As shown, for display panel 210B, brightness data 230B and panel temperature 240B of display panel 210B at target grayscale 220B are obtained, wherein brightness data 230B includes the display brightness value of display panel; then, target brightness 250B corresponding to target grayscale 220B and panel temperature 240B is found from preset mapping relationship; then, based on target brightness 250B and display brightness value in brightness data 230B, compensation brightness value corresponding to each pixel is determined, and driving data 260B is obtained based on compensation brightness value of each pixel. For example, driving data 260B may include compensation voltage value 1, compensation voltage value 2, ..., compensation voltage value n; then, driving data 260B is used to drive display panel 270B.

[0082] According to embodiments of this disclosure, the preset mapping relationship is determined using the following operations: an initial mapping relationship is created based on a sample dataset for multiple preset gray levels, wherein each sample data in the sample dataset includes sample panel temperature and sample brightness data for the preset gray levels, and the initial mapping relationship characterizes the mapping relationship between sample brightness data, preset gray levels, and sample panel temperature; the preset gray levels and sample panel temperatures of the initial mapping relationship are corrected based on their respective gray level compensation values ​​and temperature compensation values ​​for the preset gray levels to obtain the preset mapping relationship, wherein the gray level compensation value is obtained by processing the preset gray levels using a gray level compensation function, and the temperature compensation value is obtained by processing the sample panel temperature using a temperature compensation function.

[0083] Creating an initial mapping relationship based on a sample dataset with multiple preset gray levels can include, for example, creating a correspondence between sample brightness data, preset gray levels, and sample panel temperatures. Specifically, an initial mapping relationship table can be formed, where each row of the table includes a sample brightness data, a preset gray level, and a sample panel temperature. Alternatively, a function can be formed with sample brightness data as the dependent variable and preset gray levels and sample panel temperatures as independent variables, such as L1 = F(G1, T1).

[0084] Based on the respective grayscale compensation values ​​and temperature compensation values ​​for the preset grayscale, correcting the preset grayscale and sample panel temperature in the initial mapping relationship can include correcting the preset grayscale in the initial mapping relationship using the grayscale compensation values ​​and correcting the sample panel temperature in the initial mapping relationship using the temperature compensation values.

[0085] For example, the initial mapping table includes multiple rows of mapping arrays, each containing sample brightness data, a preset grayscale, and a sample panel temperature. For the m-th mapping array in the initial mapping table (m ≥ 1), for example, the m-th mapping array includes sample brightness data Lm, a preset grayscale Gm, and a sample panel temperature Tm. The preset grayscale Gm in this mapping array is processed using a grayscale compensation function to obtain a grayscale compensation value ΔG. The sample panel temperature Tm in this mapping array is processed using a temperature compensation function to obtain a temperature compensation value ΔT. Then, the preset grayscale Gm and sample panel temperature Tm are corrected using the grayscale compensation value ΔG and the temperature compensation value ΔT, respectively, resulting in a corrected grayscale of ΔG + Gm and a corrected sample panel temperature of ΔT + Tm. This completes the correction for the m-th mapping array.

[0086] Figure 3 This is a schematic diagram illustrating the determination of a preset mapping relationship according to an embodiment of the present disclosure.

[0087] like Figure 3 As shown, firstly, a sample dataset 310 is obtained, which may include multiple sample data, each of which includes sample panel temperature and sample brightness data for a preset grayscale. Then, an initial mapping relationship 320 is created based on the sample dataset 310, representing the mapping relationship between sample brightness data, preset grayscale, and sample panel temperature. Then, the preset grayscale is processed using a grayscale compensation function to obtain a grayscale compensation value 330, and the sample panel temperature is processed using a temperature compensation function to obtain a temperature compensation value 340. Afterward, the preset grayscale and sample panel temperature in the initial mapping relationship 320 are corrected using the grayscale compensation value 330 and the temperature compensation value 340, respectively, to obtain the preset mapping relationship 350.

[0088] The sample dataset can be obtained by acquiring the sample panel temperature and sample brightness data of J sample display panels at K preset gray levels, where J and K are positive integers. The J sample display panels can be display panels of the same model, for example, display panels of the same model produced in the same batch or different batches. The temperature rise of the J sample display panels at the K preset gray levels will differ, resulting in different sample brightness data. The sample panel temperature and sample brightness data of each sample display panel at each preset gray level are considered as sample data.

[0089] For example, obtain the sample panel temperature and sample brightness data of the j-th sample display panel at the k-th preset gray level to obtain sample data jk; obtain the sample panel temperature and sample brightness data of the j-th sample display panel at the k+1-th preset gray level to obtain sample data jk+1, 1≤j≤J, 1≤k≤K.

[0090] The sample dataset can also be determined by the following method: obtaining an initial sample dataset for multiple preset gray levels, wherein each sample data in the initial sample dataset includes sample panel temperature and sample brightness data for each preset gray level; and using a sample augmentation model to augment the initial sample dataset to obtain the sample dataset, wherein the sample augmentation model is obtained by training a neural network using the initial sample dataset.

[0091] According to embodiments of this disclosure, sample data augmentation is performed on an initial sample dataset using a sample augmentation model to obtain the sample dataset. This includes: inputting preset enhanced grayscale and enhanced temperature into the sample augmentation model and outputting enhanced brightness; adding the enhanced grayscale, enhanced temperature, and enhanced brightness to the initial sample dataset to obtain the sample dataset. The initial sample dataset may contain a small amount of sample data. A sample augmentation model is obtained by training a neural network using a small amount of sample data, and then sample augmentation is performed using the sample augmentation model to obtain the sample dataset.

[0092] Enhanced grayscale can be grayscale not included in the initial sample dataset. For example, if the initial sample dataset includes grayscale 100 and grayscale 120, then the enhanced grayscale can be grayscale 110. The enhanced brightness of grayscale 110 can be predicted using an enhancement model, thereby obtaining enhanced sample data, which can then be added to the initial sample dataset to enrich the sample data.

[0093] According to embodiments of this disclosure, training a neural network using an initial sample dataset includes: inputting a preset grayscale and sample panel temperature from the sample data into the neural network, and outputting a predicted brightness; adjusting the parameters of the neural network based on the difference between the predicted brightness and the sample brightness data until the difference converges.

[0094] The neural network can be any type of neural network, such as support vector machines, decision trees, random forests, etc. It should be noted that this disclosure does not limit the type of neural network.

[0095] The difference between predicted brightness and sample brightness data can be used to determine the loss value between the two using a preset loss function. The loss function can be, for example, the L1 norm loss function, the mean squared error loss function, etc. It should be noted that this disclosure does not limit the type of loss function.

[0096] Neural network algorithms possess self-learning capabilities, and a sample augmentation model is obtained by training the neural network. When enhanced grayscale and enhanced temperature are input into the sample augmentation model, the enhanced brightness can be calculated through the model's self-learning ability. Because neural network algorithms have high-speed solution capabilities, sample augmentation models can improve the sample generation speed.

[0097] Figure 4 This is a schematic diagram illustrating the determination of a sample dataset according to an embodiment of the present disclosure.

[0098] like Figure 4 As shown, firstly, the neural network 420 is trained based on the initial sample dataset 410 to obtain the sample enhancement model 430; then, the enhanced grayscale 440 and enhanced temperature 450 are input into the sample enhancement model 430, and the enhanced brightness 460 is output after processing by the sample enhancement model 430; then, the enhanced brightness 460, enhanced grayscale 440 and enhanced temperature 450 are added to the initial sample dataset 410 as enhanced sample data, and the initial sample dataset 460 is enhanced in this way repeatedly to obtain the sample dataset 470.

[0099] According to embodiments of this disclosure, the grayscale compensation function can be created based on a first polynomial, and the grayscale compensation function represents the mapping relationship between a preset grayscale and a grayscale compensation value.

[0100] The first polynomial can be one of the following: a linear polynomial, a quadratic polynomial, a cubic polynomial, etc. It should be noted that the higher the degree of the first polynomial, the more realistic the mapping relationship between the preset grayscale and the grayscale compensation value. In the example, the first polynomial can be a quadratic polynomial. For example, the grayscale compensation function could be G2 = aG1. 2 +bG1+c, where G1 is the preset gray level, G2 is the gray level after compensation of the preset gray level using the gray level compensation value △G, i.e., G2=△G+G1; a, b, c are hyperparameters.

[0101] According to embodiments of this disclosure, the temperature compensation function may be created based on a second polynomial, and the temperature compensation function characterizes the mapping relationship between the sample panel temperature and the temperature compensation value.

[0102] The second polynomial can be one of the following: a first-order polynomial, a second-order polynomial, a third-order polynomial, etc. It should be noted that the higher the degree of the second polynomial used, the more realistic the mapping relationship between the preset grayscale and the grayscale compensation value will be. In the example, the second polynomial can be a second-order polynomial. For example, the temperature compensation function could be T2 = AT1. 2 +BT1+C, where T1 is the sample panel temperature, T2 is the temperature after compensating the sample panel temperature with the temperature compensation value △T, i.e., T2=△T+T1; A, B, C are hyperparameters.

[0103] In some embodiments, the values ​​of hyperparameters a, b, c and hyperparameters A, B, C can be determined empirically.

[0104] In other embodiments, hyperparameters a, b, c and hyperparameters A, B, C can be determined by the following method: determining intermediate mapping relationships based on grayscale compensation functions, temperature compensation functions and initial mapping relationships; determining multiple function expressions containing hyperparameters a, b, c and expressions containing hyperparameters A, B, C based on sample data and intermediate mapping relationships; and solving the above function expressions to obtain the values ​​of hyperparameters a, b, c and hyperparameters A, B, C.

[0105] Figure 5 This is a schematic diagram illustrating the determination of hyperparameters according to an embodiment of the present disclosure.

[0106] like Figure 5 As shown, the grayscale compensation function 510 is G2 = aG1 2 +bG1+c, the temperature compensation function 520 is T2=AT1 2 +BT1+C, the initial mapping relationship 530 is L1=F(G1,T1); First, replace G1 and T1 in the initial mapping relationship 530 with G2 and T2 respectively, and use the grayscale compensation function 510 and the temperature compensation function 520 to represent G2 and T2, to obtain the intermediate mapping relationship 540, for example, L1=F(aG1+C). 2 +bG1+c,AT1 2 +BT1+C); then respectively, the sample data 551, for example, L 1-1 G 1-1 T 1-1 Sample data 552, for example, L 1-2 G 1-2 T 1-2 Sample data 553, for example, L 1-3 G 1-3 T 1-3 Sample data 554, for example, L 1-4 G 1-4 T 1-4 Sample data 555, for example, L 1-5 G 1-5 T 1-5 Sample data 556, for example, L 1-6 G 1-6 T 1-6 Inputting intermediate mapping relation 540 yields function expression 561, for example, L. 1-1 =F(aG 1-1 2 +bG 1-1 +c,AT 1-1 2 +BT 1-1 +C), function expression 562, for example, L 1-2 =F(aG 1-2 2 +bG1-2 +c,AT 1-2 2 +BT 1-2 +C), function expression 563, for example, L 1-3 =F(aG 1-3 2 +bG 1-3 +c,AT 1-3 2 +BT 1-3 +C), function expression 564, for example, L 1-4 =F(aG 1-4 2 +bG 1-4 +c,AT 1-4 2 +BT 1-4 +C), function expression 565, for example L 1-5 =F(aG 1-5 2 +bG 1-5 +c,AT 1-5 2 +BT 1-5 +C), function expression 566, for example, L 1-6 =F(aG 1-6 2 +bG 1-6 +c,AT 1-6 2 +BT 1-6 +C); then, based on function expressions 561, 562, 563, 564, 565, and 566, the coefficients are solved to obtain the values ​​of hyperparameters a, b, c and hyperparameters A, B, and C, 570.

[0107] According to embodiments of this disclosure, by providing a mapping relationship, when the display panel is driven using the above mapping relationship, the problem of abnormal light emission caused by temperature rise is solved, and the display panel is made close to the target light emission brightness.

[0108] Another aspect of this disclosure provides a display driving device. Figure 6 This is a block diagram of a display driving device according to an embodiment of the present disclosure.

[0109] like Figure 6 As shown, the display driving device 600 of this embodiment includes a first acquisition module 610, a determination module 620, and a driving module 630.

[0110] The first acquisition module 610 is used to acquire panel temperature and brightness data of the display panel for the target grayscale.

[0111] The determination module 620 is used to determine the target brightness for the target grayscale based on the preset mapping relationship and the panel temperature. The preset mapping relationship represents the mapping relationship between brightness data, grayscale and panel temperature for the display panel.

[0112] The driving module 630 is used to drive the display panel to display based on driving data determined based on the target brightness and brightness data.

[0113] According to embodiments of this disclosure, the preset mapping relationship is obtained by executing the following creation module and correction module.

[0114] The creation module is used to create an initial mapping relationship based on a sample dataset for multiple preset gray levels. Each sample data in the sample dataset includes sample panel temperature and sample brightness data for the preset gray levels. The initial mapping relationship represents the mapping relationship between sample brightness data, preset gray levels, and sample panel temperature.

[0115] The correction module is used to correct the preset grayscale and sample panel temperature of the initial mapping relationship according to the grayscale compensation value and temperature compensation value for the preset grayscale respectively, so as to obtain the preset mapping relationship. The grayscale compensation value is obtained by processing the preset grayscale using the grayscale compensation function, and the temperature compensation value is obtained by processing the sample panel temperature using the temperature compensation function.

[0116] According to an embodiment of this disclosure, the grayscale compensation function is created based on a first polynomial, and the grayscale compensation function represents the mapping relationship between a preset grayscale and a grayscale compensation value.

[0117] According to embodiments of this disclosure, the temperature compensation function is created based on a second polynomial, and the temperature compensation function characterizes the mapping relationship between the sample panel temperature and the temperature compensation value.

[0118] According to embodiments of this disclosure, the sample dataset is obtained by performing the following second acquisition module and sample enhancement module.

[0119] The second acquisition module is used to acquire an initial sample dataset for multiple preset gray levels, wherein each sample data in the initial sample dataset includes sample panel temperature and sample brightness data for each preset gray level.

[0120] The sample augmentation module is used to augment the initial sample dataset using a sample augmentation model to obtain a new sample dataset. The sample augmentation model is obtained by training a neural network using the initial sample dataset.

[0121] According to embodiments of this disclosure, a training module and an adjustment module may also be executed during the process of determining the sample dataset.

[0122] The training module is used to input the preset grayscale and sample panel temperature from the sample data into the neural network and output the predicted brightness.

[0123] The adjustment module is used to adjust the parameters of the neural network based on the difference between the predicted brightness and the sample brightness data until the difference converges.

[0124] According to embodiments of this disclosure, the sample enhancement module includes:

[0125] The input / output submodule is used to input preset enhanced grayscale and enhanced temperature into the sample enhancement model and output enhanced brightness.

[0126] Add a submodule to add enhanced grayscale, enhanced temperature, and enhanced brightness to the initial sample dataset to obtain the sample dataset.

[0127] According to embodiments of this disclosure, the brightness data includes the brightness value of each pixel or the display brightness value of the display panel.

[0128] According to embodiments of this disclosure, the driving module includes a determination submodule and a driving submodule.

[0129] The determination submodule is used to determine the driving data of the display panel for the target grayscale based on the target brightness and the brightness value of each pixel, or to determine the driving data of the display panel for the target grayscale based on the target brightness and the display brightness value, wherein the driving data includes the compensation voltage value of each pixel in the display panel.

[0130] The driver submodule is used to drive the display panel using driver data.

[0131] Figure 7 This is a block diagram of an apparatus for generating a preset mapping relationship according to an embodiment of the present disclosure.

[0132] like Figure 7 As shown, the generation device 700 of this embodiment includes a temperature acquisition module 710, an optical brightness acquisition module 720, a data storage module 730, and a mapping relationship generation module 740.

[0133] Temperature acquisition module 710 is used to acquire the temperature of the sample display panel at a preset grayscale.

[0134] The optical brightness acquisition module 720 is used to acquire sample brightness data of the sample display panel at a preset grayscale and sample panel temperature.

[0135] The data storage module 730 is used to store the sample panel temperature and sample brightness data collected at a preset grayscale.

[0136] The mapping relationship generation module 740 is used to generate a preset mapping relationship using the sample panel temperature and sample brightness data collected under the preset grayscale.

[0137] It should be noted that the temperature acquisition module 710 and the optical brightness acquisition module 720 correspond to the functions of the second acquisition module mentioned above, and the mapping relationship generation module 740 corresponds to the functions of the creation module and the correction module mentioned above.

[0138] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), Systems-on-Chip, Systems-on-Substrate, Systems-on-Package, Application-Specific Integrated Circuits (ASICs), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0139] For example, any plurality of the first acquisition module 610, determination module 620, and driving module 630 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the first acquisition module 610, determination module 620, and driving module 630 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first acquisition module 610, the determination module 620, and the driving module 630 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0140] It should be noted that the display driving device part in the embodiments of this disclosure corresponds to the display driving method part in the embodiments of this disclosure. For a detailed description of the display driving device part, please refer to the display driving method part, which will not be repeated here.

[0141] This disclosure provides a display panel including the display driving device described above.

[0142] Figure 8 This is a schematic diagram of a display panel according to an embodiment of the present disclosure.

[0143] like Figure 8 As shown, the display panel 800 includes a storage device 810 and a driver chip 820. The storage device 810 stores driving data determined by the display driving method provided in any embodiment of this disclosure. When the display panel 800 is displayed, the driver chip 820 of the display panel 800 obtains the driving data of the display panel 800 from the storage device 810, determines the driving signal for driving the pixels to emit light based on the driving data, and drives the display panel to display.

[0144] Figure 9 This is a block diagram of an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure. Figure 9 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0145] like Figure 9 As shown, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage portion 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0146] RAM 903 stores various programs and data required for the operation of electronic device 900. Processor 901, ROM 902, and RAM 903 are interconnected via bus 904. Processor 901 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 902 and / or RAM 903. It should be noted that the programs may also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0147] According to embodiments of this disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to a bus 904. The electronic device 900 may also include one or more of the following components connected to the input / output (I / O) interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 910 as needed so that computer programs read from it can be installed into the storage section 908 as needed.

[0148] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by processor 901, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0149] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0150] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0151] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 902 and / or RAM 903 described above and / or one or more memories other than ROM 902 and RAM 903.

[0152] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the methods provided in the embodiments of this disclosure.

[0153] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0154] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0155] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0156] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0157] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A display driving method, comprising: Obtain the panel temperature and brightness data of the display panel for the target grayscale; Based on a preset mapping relationship and the panel temperature, a target brightness for the target grayscale is determined, wherein the preset mapping relationship represents the mapping relationship between brightness data, grayscale, and panel temperature for the display panel; and The display panel is driven to display based on driving data determined according to the target brightness and the brightness data; The preset mapping relationship is determined using the following operation: An initial mapping relationship is created based on a sample dataset for multiple preset gray levels, wherein each sample data in the sample dataset includes sample panel temperature and sample brightness data for the preset gray levels, and the initial mapping relationship characterizes the mapping relationship between the sample brightness data, the preset gray levels, and the sample panel temperature; Based on the grayscale compensation value and temperature compensation value for each preset grayscale, the preset grayscale and the sample panel temperature of the initial mapping relationship are corrected respectively to obtain the preset mapping relationship. The grayscale compensation value is obtained by processing the preset grayscale using a grayscale compensation function, and the temperature compensation value is obtained by processing the sample panel temperature using a temperature compensation function.

2. The method according to claim 1, wherein, The grayscale compensation function is created based on the first polynomial, and the grayscale compensation function represents the mapping relationship between the preset grayscale and the grayscale compensation value.

3. The method according to claim 1, wherein, The temperature compensation function is created based on the second polynomial, and the temperature compensation function characterizes the mapping relationship between the sample panel temperature and the temperature compensation value.

4. The method according to claim 1, wherein, The sample dataset was determined using the following operation: Obtain an initial sample dataset for multiple preset gray levels, wherein each sample data in the initial sample dataset includes sample panel temperature and sample brightness data for each preset gray level; The initial sample dataset is augmented using a sample augmentation model to obtain the sample dataset, wherein the sample augmentation model is obtained by training a neural network using the initial sample dataset.

5. The method according to claim 4, wherein, The step of training the neural network using the initial sample dataset includes: The preset grayscale and the sample panel temperature in the sample data are input into the neural network to output the predicted brightness. Based on the difference between the predicted brightness and the sample brightness data, the parameters of the neural network are adjusted until the difference converges.

6. The method according to claim 4, wherein, The process of augmenting the initial sample dataset using a sample augmentation model to obtain the sample dataset includes: The preset enhanced grayscale and enhanced temperature are input into the sample enhancement model, and the enhanced brightness is output. The enhanced grayscale, enhanced temperature, and enhanced brightness are added to the initial sample dataset to obtain the sample dataset.

7. The method according to claim 1, wherein, The brightness data includes the brightness value of each pixel, or the brightness data includes the display brightness value of the display panel; The step of driving the display panel to display based on driving data determined according to the target brightness and the brightness data includes: Based on the target brightness and the brightness value of each pixel, the driving data of the display panel for the target grayscale is determined, or based on the target brightness and the display brightness value, the driving data of the display panel for the target grayscale is determined, wherein the driving data includes the compensation voltage value of each pixel in the display panel; The display panel is driven to display using the driving data.

8. A display driving device, comprising: The acquisition module is used to acquire the panel temperature and brightness data of the display panel for the target grayscale. The determining module is used to determine the target brightness for the target grayscale based on a preset mapping relationship and the panel temperature, wherein the preset mapping relationship represents the mapping relationship between brightness data, grayscale, and panel temperature for the display panel, and the preset mapping relationship is determined using the following operations: An initial mapping relationship is created based on a sample dataset for multiple preset gray levels, wherein each sample data in the sample dataset includes sample panel temperature and sample brightness data for the preset gray levels, and the initial mapping relationship characterizes the mapping relationship between the sample brightness data, the preset gray levels, and the sample panel temperature; Based on the grayscale compensation values ​​and temperature compensation values ​​for each preset grayscale, the preset grayscale and the sample panel temperature of the initial mapping relationship are corrected respectively to obtain the preset mapping relationship. The grayscale compensation value is obtained by processing the preset grayscale using a grayscale compensation function, and the temperature compensation value is obtained by processing the sample panel temperature using a temperature compensation function. The control module is used to drive the display panel to display based on the driving data determined based on the target brightness and the brightness data.

9. A display panel comprising the driving device of claim 8.

10. An electronic device, comprising: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 7.

11. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 7.

12. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 7.

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