Peak brightness detection method and device, equipment and storage medium

Abstract

The invention provides a peak brightness detection method and device, equipment and a storage medium, and the method comprises the steps: obtaining the estimated peak brightness corresponding to a target image, and the estimated peak brightness is the estimated peak brightness of the target image displayed by target display equipment; and inputting the estimated peak brightness into a peak brightness fitting model for correction to obtain corrected peak brightness corresponding to the target picture, the peak brightness fitting model is used for representing a corresponding relationship between the estimated peak brightness reached by the display picture of the target display equipment and the peak brightness reached by the display picture of the target display equipment detected by brightness detection equipment; and determining the corrected peak brightness as the actual peak brightness reached when the target display device displays the target picture. According to the technical scheme, automatic detection of the peak brightness of the display equipment can be realized, so that the accuracy of the peak brightness obtained through automatic detection is ensured.

Description

Technical Field

[0001] The present application relates to the field of displays, and in particular to a peak brightness detection method, device, equipment and storage medium. Background Art

[0002] Liquid crystal displays are composed of a liquid crystal panel and a backlight unit. The backlight unit emits constant and uniform light to the liquid crystal panel, and the liquid crystal panel adjusts the pixel transmittance to display different images. If the backlight unit always emits light at the same brightness, the saturation and contrast of the picture will be reduced due to light leakage from the liquid crystal panel, affecting the display effect. Therefore, dynamic dimming technology is generally used to adjust the luminous intensity of the backlight unit according to the image content that the display needs to display, so that the backlight brightness matches the image brightness, thereby improving the contrast of the picture.

[0003] Ideally, for the screen with the highest brightness, the LCD displays output at full power, that is, for each light emitting diode (LED) in the backlight unit, the LCD displays drive the LED to emit light at maximum power, so that the backlight brightness of the LCD displays reaches the maximum. In practice, due to some hardware limitations, full power output of the LCD displays will cause screen burn-in due to excessive light emitting power. In order to avoid screen burn-in, the power consumption of the display needs to be limited. A feasible solution is to adjust the backlight of the display through the backlight brightness adjustment curve and the picture so that the power consumption of the display meets the power consumption limit. Under the premise of meeting the power consumption limit, it is necessary to manually use a brightness detection instrument to repeatedly detect the peak brightness of the display and adjust the backlight brightness curve so that the peak brightness of the picture adjusted by the backlight brightness adjustment curve is as large as possible, thereby producing better results. Summary of the invention

[0004] The present application provides a peak brightness detection method, apparatus, device and storage medium to detect the peak brightness reached by a display screen.

[0005] In a first aspect, a peak brightness detection method is provided, comprising:

[0006] Obtaining an estimated peak brightness corresponding to a target picture, wherein the estimated peak brightness is an estimated peak brightness reached when a target display device displays the target picture;

[0007] The estimated peak brightness is input into a peak brightness fitting model for correction to obtain a corrected peak brightness corresponding to the target image, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the target display device display image and the peak brightness reached by the target display device display image detected by a brightness detection device;

[0008] The corrected peak brightness is determined as the actual peak brightness reached by the target display device when displaying the target picture.

[0009] In this technical solution, after obtaining the estimated peak brightness reached by the display device displaying the picture, the estimated peak brightness is corrected according to the preset corresponding relationship to obtain the corrected peak brightness of the picture, and then the corrected peak brightness of the picture is determined as the actual peak brightness reached by the display device displaying the picture, thereby realizing automatic detection of the peak brightness of the display device. After adjusting the peak brightness curve of the display device, the user can determine the peak brightness of the display device without using a brightness detection instrument, thereby improving efficiency; by inputting the estimated peak brightness into the peak brightness fitting model for correction, the corrected peak brightness is obtained, and the model can better express the corresponding relationship between the estimated peak brightness and the peak brightness detected by the brightness detection device, thereby making the corrected peak brightness more accurate and ensuring the accuracy of the peak brightness automatically detected; in addition, since the price of a high-precision brightness detection instrument is relatively expensive, the peak brightness of the display device is automatically detected by a software algorithm and the detection accuracy is ensured by a peak brightness fitting model, compared with detecting the peak brightness of the display device by a brightness detection instrument, the detection cost can also be saved.

[0010] In combination with the first aspect, in a possible implementation method, the peak brightness fitting model is obtained by training and fitting with a first brightness and a second brightness corresponding to a plurality of sample images with different brightness as training sample data, wherein the first brightness is the estimated peak brightness reached by the target display device displaying the sample image, and the second brightness is the peak brightness reached by the target display device displaying the sample image detected by a brightness detection device.

[0011] In combination with the first aspect, in a possible implementation method, before obtaining the estimated peak brightness corresponding to the target image, it also includes: using the first brightness and the second brightness corresponding to the multiple sample images with different brightness as training sample data, the first brightness is used as the input data of the training sample data, and the second brightness is used as the sample label of the training sample data; inputting the input data in the training sample data into a peak brightness fitting model to obtain the predicted brightness output by the peak brightness fitting model; calculating the error between the predicted brightness and the sample label in the training sample data; and adjusting the parameters of the peak brightness fitting model according to the error until the error is the minimum error.

[0012] In combination with the first aspect, in a possible implementation, obtaining the estimated peak brightness corresponding to the target picture includes: obtaining a backlight matrix corresponding to the target picture, the backlight matrix including backlight brightness data of each of a plurality of backlight partitions included in the target display device; and determining the estimated peak brightness according to the backlight matrix. Since the brightness of the display device is determined by the backlight brightness, it is more reasonable and effective to determine the peak brightness reached by the display device displaying the picture according to the backlight matrix corresponding to the picture.

[0013] In combination with the first aspect, in a possible implementation, determining the estimated peak brightness according to the backlight matrix includes: performing backlight diffusion on the backlight matrix to obtain a backlight diffusion matrix corresponding to the target picture, wherein the size of the backlight diffusion matrix is ​​the same as the size of the target picture; and determining the estimated peak brightness according to the backlight diffusion matrix. The backlight diffusion matrix is ​​obtained by performing backlight diffusion on the backlight matrix, and the backlight diffusion matrix can reflect the backlight condition when the display device displays the picture. Therefore, determining the estimated peak brightness according to the backlight diffusion matrix can make the estimated peak brightness close to the actual peak brightness.

[0014] In combination with the first aspect, in a possible implementation, the backlight diffusion is performed on the backlight matrix to obtain a backlight diffusion matrix corresponding to the target picture, including: taking the backlight matrix as the target matrix, performing matrix filtering on the target matrix to obtain a first matrix; performing matrix amplification on the first matrix to obtain a second matrix; taking the second matrix as the target matrix, returning to execute the step of performing matrix filtering on the target matrix to obtain the first matrix, until the size of the second matrix reaches the size of the target picture; and determining the second matrix as the backlight diffusion matrix.

[0015] In combination with the first aspect, in a possible implementation, the center of the target image contains a white window; the determining the estimated peak brightness according to the backlight diffusion matrix includes: determining the backlight brightness data of the central element of the backlight diffusion matrix as the estimated peak brightness, wherein the central element is an element located at the center of the backlight diffusion matrix. When the center of the image contains a white window, the brightness of the center of the image is the brightest, and determining the backlight brightness data of the central element in the backlight diffusion matrix that reflects the backlight condition when the display device displays the image as the estimated peak brightness can make the estimated peak brightness close to the actual peak brightness.

[0016] In combination with the first aspect, in a possible implementation method, obtaining the backlight matrix corresponding to the target picture includes: obtaining brightness characteristic values ​​corresponding to each of a plurality of partitioned pictures corresponding to the target picture, the plurality of partitioned pictures being obtained by partitioning the target picture according to the plurality of backlight partitions, the brightness characteristic values ​​including at least one of a brightness mean value, a brightness minimum value or a brightness maximum value; determining backlight brightness data of each of the plurality of backlight partitions according to the brightness characteristic values ​​corresponding to each of the plurality of partitioned pictures and a backlight brightness adjustment curve corresponding to the target display device.

[0017] In a second aspect, a peak brightness detection device is provided, comprising:

[0018] A peak brightness detection module, used to obtain an estimated peak brightness corresponding to a target picture, wherein the estimated peak brightness is the estimated peak brightness reached by a target display device when displaying the target picture;

[0019] A correction module, used for inputting the estimated peak brightness into a peak brightness fitting model for correction, so as to obtain a corrected peak brightness corresponding to the target picture, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the display picture of the target display device and the peak brightness reached by the display picture of the target display device detected by a brightness detection device;

[0020] The peak brightness determination module is used to determine the corrected peak brightness as the actual peak brightness achieved by the target display device when displaying the target picture.

[0021] In a third aspect, a display device is provided, comprising a memory, a display panel, and one or more processors, wherein the memory and the display panel are connected to the one or more processors, and the one or more processors are used to execute one or more computer programs stored in the memory. When the one or more processors execute the one or more computer programs, the display device implements the peak brightness detection method of the first aspect mentioned above.

[0022] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the peak brightness detection method of the first aspect.

[0023] The present application can achieve the following technical effects: it realizes automatic detection of the peak brightness of the display device. After the user adjusts the peak brightness curve of the display device, the peak brightness of the display device can be determined without using a brightness detection instrument, which can improve efficiency; by inputting the estimated peak brightness into the peak brightness fitting model for correction, the corrected peak brightness is obtained. The model can better express the correspondence between the estimated peak brightness and the peak brightness detected by the brightness detection device, so that the corrected peak brightness can be more accurate, ensuring the accuracy of the peak brightness obtained by automatic detection; in addition, since the price of high-precision brightness detection instruments is relatively expensive, the peak brightness of the display device is automatically detected by a software algorithm and the detection accuracy is ensured by a peak brightness fitting model. Compared with detecting the peak brightness of the display device by a brightness detection instrument, the detection cost can also be saved. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of the hardware structure of a display device provided in an embodiment of the present application;

[0026] Figure 2 A schematic diagram of a backlight brightness adjustment curve provided in an embodiment of the present application;

[0027] Figure 3 A schematic diagram of a process flow of a peak brightness detection method provided in an embodiment of the present application;

[0028] Figure 4A A schematic diagram of a target screen provided in an embodiment of the present application;

[0029] Figure 4B A schematic diagram of initial backlight brightness data provided in an embodiment of the present application;

[0030] Figure 4C A schematic diagram of a backlight matrix provided in an embodiment of the present application;

[0031] Figure 4D A schematic diagram of a backlight diffusion matrix provided in an embodiment of the present application;

[0032] Figure 5 A flowchart of a method for training a peak brightness fitting model provided in an embodiment of the present application;

[0033] Figure 6A schematic diagram of a sample screen provided in an embodiment of the present application;

[0034] Figure 7 A schematic diagram of a peak brightness fitting model provided in an embodiment of the present application;

[0035] Figure 8 is a structural schematic diagram of a peak brightness detection device provided in an embodiment of the present application;

[0036] Fig. 9 It is a structural schematic diagram of a display device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0038] It should be noted that, if there is no conflict, the various features in the embodiments of the present application can be combined with each other, all within the scope of protection of the present application. In addition, although the functional module division is performed in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a sequence different from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in this application do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0039] The technical solution of the present application is applicable to backlight brightness adjustment scenarios, wherein the technical solution of the present application can be applied to display devices.

[0040] To facilitate understanding, the structure and display principle of the display device are briefly introduced first.

[0041] See also Figure 1 , Figure 1 A schematic diagram of the hardware structure of a display device provided in an embodiment of the present application is shown in FIG. Figure 1As shown, the display 10 includes a liquid crystal panel 101, a backlight source 102, a driving circuit board 103, etc. The backlight source 102 is composed of an array of LED lamp beads, and the resolution of the display is equal to the number of LED lamp beads contained in the array of LED lamp beads. The driving circuit board 103 is provided with components such as a control chip and a driving chip. The control chip is connected to the driving chip, and the driving chip is connected to each LED lamp bead in the backlight source 102. The control chip is used to obtain the original backlight brightness data, and adjust the original backlight brightness data and send it to the driving chip. The driving chip drives and controls the brightness of each LED lamp bead in the backlight source 102 according to the adjusted backlight brightness data, thereby completing the display.

[0042] Under ideal conditions, the driver chip can drive each LED lamp bead in the backlight source 102 at maximum power to make all the LED lamp beads in the backlight source 102 bright, so that the brightness of the display reaches the maximum. This will cause the total luminous power to be too high, accelerate the aging of the pixels, and thus cause screen burn-in. In order to avoid screen burn-in, the total luminous power of the LED lamp beads in the backlight source 102 must be limited to a certain percentage of the theoretical total luminous power. One feasible solution is to adjust the backlight brightness of the display through a backlight brightness adjustment curve so that the power consumption of the display meets the limit. For example, a backlight brightness adjustment curve can be as follows: Figure 2 As shown, the abscissa of the backlight brightness adjustment curve is the brightness ratio, and the ordinate is the backlight adjustment coefficient. After the initial backlight brightness data is calculated based on the brightness of the picture, the ratio of the sum of the initial brightness backlight brightness data and the backlight brightness data when the backlight is fully lit (referring to the maximum driving power) is calculated as the brightness ratio; then the backlight adjustment coefficient corresponding to the brightness ratio is determined on the backlight brightness adjustment curve; finally, the determined backlight adjustment coefficient is multiplied by the initial backlight brightness data to obtain the final backlight brightness data. The driver chip drives and controls the brightness of each LED lamp bead in the backlight source according to the final backlight brightness data.

[0043] In order to achieve a better display effect, it is necessary to detect the peak brightness reached by the display device when displaying the picture, that is, the display brightness at the brightest position, and then adjust the backlight brightness adjustment curve according to the peak brightness, so that the peak brightness reached by the display device when displaying the picture is as large as possible while meeting the power consumption limit. Generally, it is necessary to adjust the backlight brightness adjustment curve multiple times, which means that it is necessary to detect the peak brightness reached by the display device when displaying the picture multiple times, and the process is relatively cumbersome. In addition, brightness detection equipment that can accurately detect the peak brightness of a display device is usually more expensive. Using brightness detection equipment to detect the peak brightness of a display device has a high detection cost, and it is difficult to achieve batch detection.

[0044] In view of this, the present application proposes a peak brightness detection scheme, which can realize automatic detection of the peak brightness reached by the display device screen, eliminating the manual detection step and improving the detection efficiency. In addition, the present application uses a software algorithm to detect the peak brightness reached by the display device when displaying the screen and uses a peak brightness fitting model to correct the peak brightness detected by the software algorithm. The accuracy of the peak brightness detection can be ensured without using a brightness detection device for detection, thereby saving detection costs while ensuring detection accuracy, and can perform peak brightness detection on multiple display devices at the same time to achieve batch detection.

[0045] See also Figure 3 , Figure 3 A schematic diagram of a peak brightness detection method provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the method comprises the following steps:

[0046] S201, obtaining an estimated peak brightness corresponding to a target picture.

[0047] Here, the estimated peak brightness corresponding to the target picture is the estimated peak brightness reached by the target display device displaying the target picture, the target display device is the display device that displays the target picture, and the peak brightness is the display brightness at the brightest position of the target display device when the target display device displays the target picture.

[0048] The target picture can be any picture to be displayed. In order to better measure the peak brightness reached by the target display device when displaying the picture, the target picture can be a picture containing a white window. The white window refers to a rectangular area composed of multiple white pixels. The pixel value of the white pixel is 255, that is, the white window is a rectangular area composed of pixels with a pixel value of 255. The white window can be located at the center of the target picture. For example, the picture containing the white window in the center of the picture can be as follows: Figure 4A As shown, Figure 4A The center of the screen contains a white window that accounts for 50% of the screen, that is, the size of the white window is 50% of the size of the screen.

[0049] Since white pixels are usually the brightest when displayed, the target image contains a white window. By estimating the peak brightness of the white window, the peak brightness achieved by the target display device when displaying the image can be accurately estimated.

[0050] Since the display brightness of the display device is determined by the backlight brightness, the peak brightness reached by the display device can be determined according to the backlight matrix corresponding to the picture. The estimated peak brightness corresponding to the target picture can be obtained through the following steps A1-A2:

[0051] A1. Get the backlight matrix corresponding to the target image.

[0052] Here, the backlight matrix corresponding to the target picture includes the backlight brightness data of each of the multiple backlight partitions included in the target display device. The backlight partition refers to the area where the target display device performs independent light control. For example, the backlight light source in the target display device is divided into 24*20 (a total of 480) backlight partitions, and the backlight matrix corresponding to the target picture includes 24*20 backlight brightness data. The backlight brightness data contained in the backlight matrix corresponding to the target picture is the final backlight brightness data introduced above.

[0053] Among them, the target screen can be divided into multiple partitioned screens according to the multiple backlight partitions included in the target display device, one partitioned screen corresponds to one backlight partition, and then multiple backlight brightness data are determined according to the brightness of the multiple partitioned screens, so as to obtain the backlight matrix corresponding to the target screen. For example, if the target display device includes 24*20 (a total of 480) backlight partitions, the target screen can be divided into 24*20 partitioned screens, and then 24*20 backlight brightness data are determined according to the brightness of the 24*20 partitioned screens.

[0054] In a feasible implementation manner, the backlight matrix corresponding to the target image may be obtained through the following steps A11-A12:

[0055] A11. Obtain brightness characteristic values ​​corresponding to each of the plurality of subarea pictures corresponding to the target picture.

[0056] Here, the multiple sub-area screens corresponding to the target screen are obtained by partitioning the target screen according to the multiple backlight partitions of the target display device. The multiple sub-area screens corresponding to the target screen may be, for example, the aforementioned 24*20 sub-area screens.

[0057] The pixel brightness characteristic value corresponding to the partitioned picture is used to represent a certain brightness characteristic of the partitioned picture, and the pixel brightness characteristic value corresponding to the partitioned picture may include at least one of the pixel brightness mean value, the pixel brightness minimum value, and the pixel brightness maximum value of the partitioned picture.

[0058] The average pixel brightness corresponding to the partition screen refers to the average brightness of each pixel in the partition screen, the maximum pixel brightness corresponding to the partition screen refers to the maximum brightness of each pixel in the partition screen, and the minimum pixel brightness corresponding to the partition screen refers to the minimum brightness of each pixel in the partition screen. The average pixel brightness, maximum pixel brightness, and minimum pixel brightness corresponding to the partition screen can be obtained by the following formula:

[0059]

[0060] L2=max(l i )

[0061] L3=min(li )

[0062] Among them, l i is the brightness of the i-th pixel in the partitioned picture, n is the total number of pixels contained in the partitioned picture, L1 is the average pixel brightness corresponding to the partitioned picture, L2 is the maximum pixel brightness corresponding to the partitioned picture, and L3 is the minimum pixel brightness corresponding to the partitioned picture.

[0063] For each partition screen corresponding to the target screen, the brightness of each pixel in the partition screen can be determined, and then the average brightness of each pixel in the partition screen can be calculated to obtain the average pixel brightness corresponding to the partition screen; the maximum value of the brightness of each pixel in the partition screen can also be determined to obtain the maximum pixel brightness corresponding to the target partition screen; the minimum value of each pixel in the partition screen can also be determined.

[0064] A12. Determine the backlight brightness data of each of the multiple backlight partitions included in the target display device based on the brightness characteristic values ​​corresponding to each of the multiple partitioned images corresponding to the target image and the backlight brightness adjustment curve corresponding to the target display device.

[0065] Here, the backlight brightness adjustment curve corresponding to the target display device is an adjustment curve for adjusting the backlight brightness of the target display device. Exemplarily, the backlight brightness adjustment curve corresponding to the target display device can be as follows: Figure 2 shown.

[0066] Among them, the initial backlight brightness data corresponding to the multiple sub-screens corresponding to the target screen can be determined according to the brightness characteristic values ​​corresponding to each of the multiple sub-screens corresponding to the target screen, and then the ratio between the sum of the initial backlight brightness data corresponding to the multiple sub-screens corresponding to the target screen and the sum of the backlight brightness data when the backlight is fully lit is calculated as the brightness ratio corresponding to the target screen; then, the target backlight brightness adjustment coefficient corresponding to the brightness ratio corresponding to the target screen is determined on the backlight brightness adjustment curve corresponding to the target display device, and finally, the target backlight adjustment coefficient is multiplied by the initial backlight brightness data corresponding to each of the multiple sub-screens corresponding to the target screen to obtain the backlight brightness data corresponding to each of the multiple backlight sub-screens contained in the target display device.

[0067] For example, for Figure 4A Assume that the target display device includes 480 backlight partitions. The initial backlight brightness data corresponding to the multiple partitioned screens corresponding to the target screen can be as follows: Figure 4B As shown, it contains 480 initial backlight brightness data, using Figure 2 After the initial backlight brightness data is processed by the backlight brightness adjustment curve shown in FIG. Figure 4CAs shown, it contains 480 final backlight brightness data. Figure 4C That is, the backlight brightness data corresponding to each of the multiple backlight partitions contained in the target display device, that is, Figure 4C for Figure 4A The backlight matrix corresponding to the target image shown.

[0068] The sum of the backlight brightness data when the backlight is fully on is equal to the product of the number of backlight partitions included in the target display device and the maximum brightness of the backlight partitions. For example, if the target display device includes 480 backlight partitions, and each backlight partition can reach the maximum backlight brightness of 255 (i.e., the maximum brightness), the sum of the backlight brightness data when the backlight is fully on is 480*255.

[0069] Among them, after calculating the brightness characteristic values ​​corresponding to each of the multiple sub-screens corresponding to the target screen, for each sub-screen corresponding to the target screen, the pixel brightness mean and the pixel brightness maximum corresponding to the sub-screen can be weighted and summed to obtain the initial backlight brightness data corresponding to the sub-screen, thereby obtaining the initial backlight brightness data corresponding to each of the multiple sub-screens corresponding to the target screen. The weight values ​​corresponding to the pixel brightness mean and the pixel brightness maximum can be determined based on experiments. Exemplarily, the weight of the pixel brightness mean can be 0.3, and the weight of the pixel brightness maximum can be 0.7, then the initial backlight brightness data corresponding to the sub-screen L4 = 0.3*L1+0.7*L2. The ideal backlight brightness of the sub-screen is determined according to the pixel brightness mean and the pixel brightness maximum of the sub-screen, taking into account the existence of the brightest pixel in the sub-screen, so that the brightness of the backlight partition can match the average brightness and maximum brightness of the screen, thereby improving the contrast of the screen.

[0070] Optionally, the initial backlight brightness data corresponding to each of the multiple subarea screens corresponding to the target screen may also be determined in other ways. For example, the initial backlight brightness data of the subarea screen may also be determined based on the global average brightness of the target screen and the mean pixel brightness of the subarea screen; or, the maximum pixel brightness of the subarea screen may also be determined as the initial backlight brightness data of the subarea screen; or, the maximum pixel brightness, the minimum pixel brightness and the mean pixel brightness of the subarea screen may also be weighted summed to obtain the initial backlight brightness data of the subarea screen; or, the minimum pixel brightness and the mean pixel brightness of the subarea screen may also be weighted summed to obtain the initial backlight brightness data of the subarea screen, and so on, not limited to the description here. This application is not limited.

[0071] A2. Determine the estimated peak brightness corresponding to the target picture according to the backlight matrix corresponding to the target picture.

[0072] In a feasible implementation manner, the maximum backlight brightness data in the backlight matrix may be determined as the estimated peak brightness corresponding to the target picture.

[0073] In another feasible implementation manner, the estimated peak brightness corresponding to the target picture may also be determined through the following steps A21-A22:

[0074] A21. Perform backlight diffusion on the backlight matrix corresponding to the target picture to obtain a backlight diffusion matrix corresponding to the target picture.

[0075] Here, the size of the backlight diffusion matrix corresponding to the target picture is the same as the size of the target picture, that is, the same as the resolution of the target display device. For example, if the size of the target picture is 1920*1080, then the size of the backlight diffusion matrix is ​​also 1920*1080, that is, the backlight diffusion matrix includes 1920*1080 backlight brightness data. Figure 4C The backlight matrix shown in FIG. 1 is subjected to backlight diffusion to obtain a backlight diffusion matrix. Figure 4D shown.

[0076] The backlight matrix corresponding to the target image can be diffused through the following steps (1) to (6) to obtain the backlight diffusion matrix corresponding to the target image:

[0077] (1) The backlight matrix corresponding to the target image is used as the target matrix.

[0078] (2) Perform matrix filtering on the target matrix to obtain the first matrix.

[0079] Here, the target matrix and the low-pass filter template can be subjected to matrix operation to implement matrix filtering on the target matrix to obtain the first matrix. The low-pass filter template includes but is not limited to a neighborhood operator, a Gaussian filter template, and the like.

[0080] (3) Perform matrix enlargement on the first matrix to obtain a second matrix.

[0081] The first matrix may be enlarged by bilinear interpolation to obtain the second matrix.

[0082] (4) Determine whether the size of the second matrix reaches the size of the target screen.

[0083] If the size of the second matrix does not reach the size of the target screen, it means that further diffusion is required, and step (5) is executed; if the size of the second matrix reaches the size of the target screen, it means that a backlight diffusion matrix that meets the requirements has been obtained, and step (6) is executed.

[0084] (5) Use the second matrix as the target matrix and return to execute step (2).

[0085] (6) The second matrix is ​​determined as the backlight diffusion matrix.

[0086] A21. Determine the estimated peak brightness corresponding to the target image according to the backlight diffusion matrix.

[0087] In a feasible implementation, the maximum backlight brightness data in the backlight diffusion matrix can be determined as the estimated peak brightness corresponding to the target picture. For example, if the backlight diffusion matrix includes 1920*1080 backlight brightness data, the maximum backlight brightness data among the 1920*1080 backlight brightness data can be determined as the estimated peak brightness corresponding to the target picture.

[0088] When the target image contains a white window at the center of the image, the backlight brightness data of the central element of the backlight diffusion matrix can be determined as the estimated peak brightness corresponding to the target image, and the central element is the element located at the center of the backlight diffusion matrix. For example, the backlight diffusion matrix includes 1920*1080 backlight brightness data, and the backlight brightness data at the position of the 965th row and 540th column in the backlight diffusion matrix can be determined as the estimated peak brightness corresponding to the target image. When the center of the image contains a white window, the brightness of the center of the image is the brightest. The backlight brightness data of the central element in the backlight diffusion matrix that reflects the backlight condition when the display device displays the image is determined as the estimated peak brightness, which can make the estimated peak brightness close to the actual peak brightness.

[0089] Optionally, when the target image contains a white window at the center of the image, the mean value of the backlight brightness data in the area corresponding to the white window in the backlight diffusion matrix can also be used as the estimated peak brightness corresponding to the target image. Figure 4A As shown in the figure, the backlight diffusion matrix corresponding to the target image is as follows Figure 4D As shown, you can Figure 4D in Figure 4A The average value of the backlight brightness data in the area corresponding to the white window is determined as the estimated peak brightness corresponding to the target picture.

[0090] The backlight diffusion matrix is ​​obtained by backlight diffusion of the backlight matrix. The backlight diffusion matrix can reflect the backlight conditions when the display device displays a picture. Therefore, the estimated peak brightness is determined according to the backlight diffusion matrix, which can make the estimated peak brightness close to the actual peak brightness.

[0091] S202: input the estimated peak brightness corresponding to the target picture into a peak brightness fitting model for correction, to obtain a corrected peak brightness corresponding to the target picture.

[0092] Here, the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the display screen of the target display device and the peak brightness reached by the display screen of the target display device detected by the brightness detection device.

[0093] The peak brightness fitting model is obtained by training and fitting the first brightness and the second brightness corresponding to multiple sample images with different brightness as training sample data, the first brightness is the estimated peak brightness reached by the target display device displaying the sample image, and the second brightness is the peak brightness reached by the target display device displaying the sample image detected by the brightness detection device. The first brightness can be obtained by estimating the peak brightness of the multiple sample images with different brightness in the manner described in step S201 above, and the second brightness can be obtained by detecting the peak brightness of the multiple sample images with different brightness by the brightness detection device. One training sample data consists of the first brightness and the second brightness corresponding to one sample image.

[0094] The peak brightness fitting model can be any machine learning model, including but not limited to a neural network model, a support vector machine regression model, a decision tree regression model, a random forest regression model, a convolutional neural network regression model, etc., and the embodiments of the present application do not make specific limitations on this.

[0095] Since the method of training and fitting to obtain the peak brightness fitting model is different from the specific structure of the peak brightness fitting model, the principle of the peak brightness fitting model to correct the estimated peak brightness corresponding to the target image to obtain the corrected peak brightness corresponding to the target image is different. For the specific process of training and fitting to obtain the peak brightness fitting model, please refer to the subsequent Figure 5 Description of the corresponding technical solution.

[0096] S203: Determine the corrected peak brightness corresponding to the target picture as the actual peak brightness reached by the target display device when displaying the target picture.

[0097] In the above Figure 3In the corresponding technical solution, after obtaining the estimated peak brightness reached by the display device displaying the picture, the estimated peak brightness is corrected according to the preset corresponding relationship to obtain the corrected peak brightness of the picture, and then the corrected peak brightness of the picture is determined as the actual peak brightness reached by the display device displaying the picture, thereby realizing automatic detection of the peak brightness of the display device. After adjusting the peak brightness curve of the display device, the user can determine the peak brightness of the display device without using a brightness detection instrument, thereby improving efficiency; by inputting the estimated peak brightness into the peak brightness fitting model for correction, the corrected peak brightness is obtained, and the model can better express the corresponding relationship between the estimated peak brightness and the peak brightness detected by the brightness detection device, thereby making the corrected peak brightness more accurate and ensuring the accuracy of the peak brightness automatically detected; in addition, since the price of a high-precision brightness detection instrument is relatively expensive, the peak brightness of the display device is automatically detected by a software algorithm and the detection accuracy is ensured by a peak brightness fitting model, which can save detection costs compared to detecting the peak brightness of the display device by a brightness detection instrument.

[0098] Before the above step S201, a peak brightness fitting model may be pre-trained based on sample images with different brightnesses. The following describes a method for training a peak brightness fitting model.

[0099] See also Figure 5 , Figure 5 A flow chart of a method for training a peak brightness fitting model provided in an embodiment of the present application is shown as follows: Figure 5 As shown, the following steps are included:

[0100] S301, obtaining a first brightness and a second brightness of a sample picture.

[0101] Here, the sample picture refers to a picture used as a training sample. For the meaning of the first brightness and the second brightness, please refer to the description of the aforementioned step S202.

[0102] There may be multiple sample images, and the brightness of the multiple sample images is different.

[0103] In some possible cases, the sample picture may be a picture containing a white window in the center of the picture, and the sizes of the white windows contained in different sample pictures are different. For example, the sample picture may include: Figure 6 The sample pictures shown are pictures with white windows accounting for 5% to 100%. The picture with a white window in the center is used as the sample picture to estimate and detect the peak brightness of the sample picture, thereby obtaining the first brightness and the second brightness.

[0104] For each sample picture, the estimated peak brightness corresponding to the sample picture can be obtained by the method introduced in the aforementioned step S201, and used as the first brightness of the sample picture; for each sample picture, the peak brightness corresponding to the sample picture can be detected by a brightness detection device, and used as the second brightness of the sample picture.

[0105] S302: Use the first brightness and the second brightness of the sample picture as training sample data.

[0106] Here, the first brightness of the sample picture is used as input data in the training sample data, and the second brightness of the sample picture is used as the sample label of the training sample data. The training sample data can be expressed as Di = (Xi, Yi), i = 1, 2, ..., N, where N is the number of training sample data. Figure 6 As shown in the example, N is 20. Xi is the first brightness of the sample picture, and Yi is the second brightness of the sample picture.

[0107] S303, performing training fitting on the training sample data to obtain a peak brightness fitting model.

[0108] Here, training and fitting the training sample data to obtain the peak brightness fitting model means inputting the input data in the training sample data into the peak brightness fitting model, and continuously adjusting the parameters of the peak brightness fitting model so that the output of the peak brightness fitting model is infinitely close to the sample label of the training sample data, thereby learning the correlation between the input data and the sample label in the training sample data. The method of training and fitting the peak brightness fitting model to obtain the peak brightness fitting model will be different depending on the model structure of the peak brightness fitting model.

[0109] The following takes the peak brightness fitting model as a back propagation (BP) neural network model as an example to introduce a method for training to obtain the peak brightness fitting model.

[0110] The specific structure of the peak brightness fitting model can be as follows Figure 7As shown, it includes an input layer, a hidden layer and an output layer, and the hidden layer contains 5 neurons. The input layer can be represented as Xi, and the output of the hidden layer is represented as f1, f1=G1(W1*Xi+b1), W1 represents the weight matrix between the hidden layer and the input layer, W1 is a 5×1 matrix, Xi represents the input data, that is, the first brightness, b1 represents the bias parameter between the hidden layer and the input layer, b1 is a 5-dimensional column vector, G1 represents the activation function between the hidden layer and the input layer, for example, it can be a sigmoid function, and the activation function is used to introduce nonlinear characteristics to neurons and increase the representation and fitting capabilities of the neural network; the output of the output layer can be represented as f2, f2=G2(W2*f1+b2), W2 represents the weight matrix between the output layer and the hidden layer, W2 is a 1×5 matrix, b2 represents the bias parameter between the output layer and the hidden layer, and G2 represents the activation function between the output layer and the hidden layer.

[0111] The training process for the peak brightness fitting model is as follows:

[0112] Randomly select one or more training sample data Di, and input the input data Xi of Di in the training sample data into Figure 7 The peak brightness fitting model in the peak brightness fitting model is used to obtain the predicted brightness yi output by the peak brightness fitting model, yi=f2=G2(W2*f1+b2), f1=G1(W1*Xi+b1), and the mean square error between yi and the sample label Yi in the training sample data is calculated; W1, W2, b1 and b2 in the peak brightness fitting model are reversely adjusted according to the mean square error to complete a training. After multiple adjustment iterations, the final W1, W2, b1 and b2 are obtained until the mean square error is minimized.

[0113] For example, W1, W2, b1 and b2 in the peak brightness fitting model obtained after multiple adjustment iterations may be as follows:

[0114]

[0115]

[0116]

[0117] b2=1.330834667

[0118] The above parameters are parameters determined by training and fitting the backlight brightness data of the central element of the backlight diffusion matrix as the first brightness and the second brightness detected by the brightness detection device.

[0119] After training and fitting to obtain the peak brightness fitting model, the parameters (W1, W2, b1, b2) of the above-mentioned peak brightness fitting model are saved. After obtaining the estimated peak brightness corresponding to the target picture through the above-mentioned step S201, the corrected peak brightness corresponding to the target picture can be calculated according to the above-mentioned formulas f1=G1(W1*Xi+b1) and f2=G2(W2*f1+b2), thereby determining the actual peak brightness reached by the target display device when displaying the target picture.

[0120] The method of the present application is introduced above, and the device of the present application is introduced below.

[0121] See also Figure 8 , Figure 8 Schematic diagram of a peak brightness detection device provided in an embodiment of the present application. Figure 8 As shown, the peak brightness detection device 40 includes:

[0122] A peak brightness detection module 401 is used to obtain an estimated peak brightness corresponding to a target picture, where the estimated peak brightness is the estimated peak brightness reached by a target display device displaying the target picture;

[0123] A correction module 402 is used to input the estimated peak brightness into a peak brightness fitting model for correction to obtain a corrected peak brightness corresponding to the target image, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the target display device display image and the peak brightness reached by the target display device display image detected by a brightness detection device;

[0124] The peak brightness determination module 403 is used to determine the corrected peak brightness as the actual peak brightness achieved by the target display device when displaying the target picture.

[0125] In one possible design, the peak brightness fitting model is obtained by training and fitting using the first brightness and the second brightness corresponding to multiple sample images with different brightness as training sample data, wherein the first brightness is the estimated peak brightness reached by the target display device displaying the sample image, and the second brightness is the peak brightness reached by the target display device displaying the sample image detected by a brightness detection device.

[0126] In a possible design, the peak brightness detection device also includes a training module 404, which is used to use the first brightness and the second brightness corresponding to the multiple sample images with different brightness as training sample data, the first brightness is used as the input data of the training sample data, and the second brightness is used as the sample label of the training sample data; input the input data in the training sample data into the peak brightness fitting model to obtain the predicted brightness output by the peak brightness fitting model; calculate the error between the predicted brightness and the sample label in the training sample data; and adjust the parameters of the peak brightness fitting model according to the error until the error is the minimum error.

[0127] In a possible design, the peak brightness detection module 401 is specifically used to: obtain a backlight matrix corresponding to the target image, wherein the backlight matrix includes backlight brightness data of each of a plurality of backlight partitions included in the target display device; and determine the estimated peak brightness according to the backlight matrix.

[0128] In one possible design, the peak brightness detection module 401 is specifically used to: perform backlight diffusion on the backlight matrix to obtain a backlight diffusion matrix corresponding to the target picture, wherein the size of the backlight diffusion matrix is ​​the same as the size of the target picture; and determine the estimated peak brightness based on the backlight diffusion matrix.

[0129] In a possible design, the peak brightness detection module 401 is specifically used to: take the backlight matrix as the target matrix, perform matrix filtering on the target matrix to obtain a first matrix; perform matrix amplification on the first matrix to obtain a second matrix; take the second matrix as the target matrix, return to execute the step of performing matrix filtering on the target matrix to obtain the first matrix, until the size of the second matrix reaches the size of the target screen; determine the second matrix as the backlight diffusion matrix.

[0130] In one possible design, the target image contains a white window in the center of the image; the peak brightness detection module 401 is specifically used to: determine the backlight brightness data of the central element of the backlight diffusion matrix as the estimated peak brightness, and the central element is the element located at the center of the backlight diffusion matrix.

[0131] In one possible design, the peak brightness detection module 401 is specifically used to: obtain the brightness characteristic values ​​corresponding to each of the multiple partitioned screens corresponding to the target screen, wherein the multiple partitioned screens are obtained by partitioning the target screen according to the multiple backlight partitions, and the brightness characteristic values ​​include at least one of the brightness mean, the brightness minimum or the brightness maximum; determine the backlight brightness data of each of the multiple backlight partitions according to the brightness characteristic values ​​corresponding to each of the multiple partitioned screens and the backlight brightness adjustment curve corresponding to the target display device.

[0132] It should be noted that Figure 8 For the contents not mentioned in the corresponding embodiments, please refer to the description of the aforementioned method embodiments, which will not be repeated here.

[0133] After obtaining the estimated peak brightness reached by the display device displaying the picture, the above-mentioned device corrects the estimated peak brightness according to the preset corresponding relationship to obtain the corrected peak brightness of the picture, and then determines the corrected peak brightness of the picture as the actual peak brightness reached by the display device displaying the picture, thereby realizing automatic detection of the peak brightness of the display device. After the user adjusts the peak brightness curve of the display device, the peak brightness of the display device can be determined without using a brightness detection instrument, which can improve efficiency; by inputting the estimated peak brightness into the peak brightness fitting model for correction, the corrected peak brightness is obtained, and the model can better express the corresponding relationship between the estimated peak brightness and the peak brightness detected by the brightness detection device, thereby making the corrected peak brightness more accurate and ensuring the accuracy of the peak brightness automatically detected; in addition, since the price of a high-precision brightness detection instrument is relatively expensive, the peak brightness of the display device is automatically detected by a software algorithm and the detection accuracy is ensured by a peak brightness fitting model, which can save detection costs compared to detecting the peak brightness of the display device by a brightness detection instrument.

[0134] See also Fig. 9 , Fig. 9 is a schematic diagram of the structure of a display device provided in an embodiment of the present application, wherein the display device 50 includes a processor 501, a memory 502, and a display panel 503. The memory 502 and the display panel 503 are connected to the processor 501, for example, via a bus.

[0135] The processor 501 is configured to support the display device 50 to perform the corresponding functions in the method in the above method embodiment. The processor 501 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0136] The memory 502 is used to store program codes, etc. The memory 502 may include a volatile memory (VM), such as a random access memory (RAM); the memory 502 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 502 may also include a combination of the above-mentioned types of memories.

[0137] The display panel 503 is used to display images.

[0138] The processor 501 may call the program code to perform the following operations:

[0139] Obtaining an estimated peak brightness corresponding to a target picture, wherein the estimated peak brightness is an estimated peak brightness reached when a target display device displays the target picture;

[0140] The estimated peak brightness is input into a peak brightness fitting model for correction to obtain a corrected peak brightness corresponding to the target image, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the target display device display image and the peak brightness reached by the target display device display image detected by a brightness detection device;

[0141] The corrected peak brightness is determined as the actual peak brightness reached by the target display device when displaying the target picture.

[0142] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method described in the above embodiment.

[0143] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0144] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A peak brightness detection method, comprising: Obtaining an estimated peak brightness corresponding to a target picture, wherein the estimated peak brightness is an estimated peak brightness reached when a target display device displays the target picture; The estimated peak brightness is input into a peak brightness fitting model for correction to obtain a corrected peak brightness corresponding to the target image, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the target display device display image and the peak brightness reached by the target display device display image detected by a brightness detection device; The corrected peak brightness is determined as the actual peak brightness reached by the target display device when displaying the target picture.

2. The method according to claim 1, characterized in that The peak brightness fitting model is obtained by training and fitting with the first brightness and the second brightness corresponding to multiple sample images with different brightness as training sample data, wherein the first brightness is the estimated peak brightness reached by the target display device displaying the sample image, and the second brightness is the peak brightness reached by the target display device displaying the sample image detected by a brightness detection device.

3. The method according to claim 2, characterized in that Before obtaining the estimated peak brightness corresponding to the target picture, the method further includes: Using the first brightness and the second brightness corresponding to the plurality of sample images with different brightness as training sample data, wherein the first brightness is used as input data of the training sample data, and the second brightness is used as a sample label of the training sample data; Inputting the input data in the training sample data into a peak brightness fitting model to obtain a predicted brightness output by the peak brightness fitting model; Calculating the error between the predicted brightness and the sample label in the training sample data; The parameters of the peak brightness fitting model are adjusted according to the error until the error is the minimum error.

4. The method according to any one of claims 1 to 3, characterized in that: The obtaining of the estimated peak brightness corresponding to the target picture includes: Acquire a backlight matrix corresponding to the target picture, wherein the backlight matrix includes backlight brightness data of each of a plurality of backlight partitions included in the target display device; The estimated peak brightness is determined based on the backlight matrix.

5. The method according to claim 4, characterized in that The step of determining the estimated peak brightness according to the backlight matrix comprises: Performing backlight diffusion on the backlight matrix to obtain a backlight diffusion matrix corresponding to a target picture, wherein a size of the backlight diffusion matrix is ​​the same as a size of the target picture; The estimated peak brightness is determined according to the backlight diffusion matrix.

6. The method according to claim 5, characterized in that The backlight diffusion is performed on the backlight matrix to obtain a backlight diffusion matrix corresponding to the target picture, including: Taking the backlight matrix as a target matrix, performing matrix filtering on the target matrix to obtain a first matrix; Performing matrix amplification on the first matrix to obtain a second matrix; Taking the second matrix as the target matrix, returning to the step of performing matrix filtering on the target matrix to obtain the first matrix, until the size of the second matrix reaches the size of the target picture; The second matrix is ​​determined as the backlight diffusion matrix.

7. The method according to claim 5, characterized in that The target image has a white window at its center; The step of determining the estimated peak brightness according to the backlight diffusion matrix includes: The backlight brightness data of the central element of the backlight diffusion matrix is ​​determined as the estimated peak brightness, and the central element is an element located at the center of the backlight diffusion matrix.

8. The method according to claim 4, characterized in that The obtaining of a backlight matrix corresponding to the target picture includes: Acquire brightness characteristic values ​​corresponding to each of a plurality of subarea pictures corresponding to the target picture, wherein the plurality of subarea pictures are obtained by partitioning the target picture according to the plurality of backlight subareas, and the brightness characteristic values ​​include at least one of a brightness mean value, a brightness minimum value, or a brightness maximum value; The backlight brightness data of each of the plurality of backlight partitions are determined according to the brightness characteristic values ​​corresponding to each of the plurality of partitioned images and the backlight brightness adjustment curve corresponding to the target display device.

9. A peak brightness detection device, characterized in that: include: A peak brightness detection module, used to obtain an estimated peak brightness corresponding to a target picture, wherein the estimated peak brightness is the estimated peak brightness reached by a target display device displaying the target picture; A correction module, used for inputting the estimated peak brightness into a peak brightness fitting model for correction, so as to obtain a corrected peak brightness corresponding to the target picture, wherein the peak brightness fitting model is used to characterize the correspondence between the estimated peak brightness reached by the display picture of the target display device and the peak brightness reached by the display picture of the target display device detected by a brightness detection device; The peak brightness determination module is used to determine the corrected peak brightness as the actual peak brightness achieved by the target display device displaying the target picture.

10. A display device, characterized in that: The device comprises a memory, a processor and a display panel, wherein the memory and the display panel are connected to the processor, the display panel is used to display images, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the display device implements the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 8.

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