Light distribution data calibration method, device, equipment, storage medium and program product

Abstract

The application provides a light distribution data calibration method, device, equipment, storage medium and program product. The method comprises the following steps: acquiring a test image of a display device when a plurality of lamp beads are lighted up, and the adjacent lamp beads among the plurality of lamp beads are spaced apart by unlighted lamp beads; calculating a light distribution influence value of each lighted lamp bead on other lighted lamp beads based on the test brightness of each lamp bead in the test image; and obtaining light distribution data of each lighted lamp bead of the display device based on initial light distribution data of each lighted lamp bead read from the test image and the light distribution influence value. The light distribution of each lamp bead is calibrated by using image vision and the law of mutual influence among the lamp beads, and the accuracy and efficiency are high.

Description

Technical Field

[0001] This application relates to the field of backlight display technology, and in particular to a method, apparatus, device, storage medium, and program product for calibrating light distribution data. Background Technology

[0002] Mini LED backlighting technology uses individually controllable, array-distributed miniature LEDs as a backlight source, significantly improving screen brightness and contrast. Mini LED backlighting, combined with LCD (Liquid Crystal Display) technology, is widely used in end products.

[0003] Some advanced Mini LED display algorithms, such as local dimming technology, require pixel-level compensation to improve display quality and accuracy. Pixel-level compensation algorithms rely on stored light distribution data of each LED on the Mini LED display panel. How to accurately and quickly acquire this light distribution data is a problem that urgently needs to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, device, storage medium, and program product for calibrating light distribution data. It utilizes image vision algorithms to calibrate the light distribution data of multiple LEDs at once, achieving high accuracy and efficiency.

[0005] In a first aspect, this application provides a method for calibrating light distribution data, including:

[0006] Acquire a test image of the display device when multiple LEDs are lit, wherein adjacent lit LEDs are spaced apart by unlit LEDs.

[0007] Based on the test brightness of each of the multiple LEDs in the test image, calculate the influence value of each lit LED on the light distribution of the other lit LEDs;

[0008] Based on the initial light distribution data of each lit LED bead read from the test image and the light distribution influence value, the light distribution data of each lit LED bead of the display device is obtained.

[0009] Optionally, acquiring test images of the display device when multiple LEDs are lit includes:

[0010] When lighting up multiple LEDs on each panel of the display device in batches, a test image of the display device is acquired by an image acquisition device when multiple LEDs are lit in each batch. The multiple LEDs lit up in different batches are different.

[0011] Optionally, when lighting up multiple LEDs on each panel of the display device in batches, a test image of the display device is acquired by an image acquisition device when multiple LEDs are lit in each batch, including:

[0012] Based on the images of each panel of at least one display device when some of the LEDs are lit, determine the cropping area of ​​each panel;

[0013] When lighting up multiple LED beads on each panel in batches, the image to be segmented of the at least one display device is acquired by an image acquisition device when multiple LED beads are lit in each batch.

[0014] Test images of each panel are obtained from the image to be segmented by cropping the area of ​​each panel.

[0015] Optionally, the step of calculating the influence of each lit LED on the light distribution of the other lit LEDs based on the test brightness of each LED in the test image includes:

[0016] For each of the plurality of LED beads, the test brightness of that LED bead is determined based on the test image;

[0017] Based on the tested brightness of the LED and the stored weight matrix, the influence of the LED on the light distribution of other lit LEDs is determined.

[0018] Optionally, the light distribution data of the LED includes light distribution data of the central region and light distribution data of the non-central region. The scope of the light distribution influence value is the central region. The calculation of the light distribution influence value of the LED on the central region of other lit LEDs, based on the LED's test brightness and the stored weight matrix, includes:

[0019] For other LEDs lit in the same test image as the LED, the influence value of the LED on the light distribution of the central region of the other LEDs is determined based on the LED's test brightness, the stored weight matrix of the LED, and the positional offset of the other LEDs relative to the LED.

[0020] Optionally, obtaining the light distribution data of each illuminated LED in the display device based on the initial light distribution data of each illuminated LED read from the test image and the light distribution influence value includes:

[0021] For each of the plurality of LED beads, based on the test image, the initial light distribution data of the central region of that LED bead is determined;

[0022] Based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead, the light distribution data of the central region of the LED bead is determined.

[0023] Based on the tested brightness of the LED and the stored weight matrix of the LED, the light distribution data of the non-central region of the LED is determined.

[0024] Optionally, determining the light distribution data of the central region of the LED bead based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead includes:

[0025] The light distribution data of the central region of the LED bead is determined as the difference between the initial light distribution data of the central region of the LED bead and the sum of the influence values ​​of the other LED beads lit on the light distribution of the central region of the LED bead.

[0026] Optionally, the method further includes:

[0027] The light distribution data of the central and non-central regions of the LED beads are compressed to obtain compressed light distribution data.

[0028] Store the compressed light distribution data.

[0029] Optionally, before acquiring a test image of the display device with multiple LEDs lit, the method further includes:

[0030] Acquire test images of multiple sample display devices when at least one LED bead is lit, wherein the sample display devices are of the same model as the display device;

[0031] Based on the test images of the sample display device, the test brightness of the lit LED beads and the light distribution data of the non-central area are determined;

[0032] Based on the test brightness of the lit LEDs and the light distribution data of the non-central area, the weight matrix of the lit LEDs is determined.

[0033] The average value of the weight matrices of the illuminated LEDs at the same position in the multiple sample display devices is used as the weight matrix of the LEDs at that position in the display device.

[0034] Optionally, the number of unlit LEDs between adjacent lit LEDs is a preset number, and the method further includes:

[0035] The lower limit of the preset number is determined based on the size of the central area of ​​the LED beads in the display device and the spacing between adjacent LED beads in the display device.

[0036] Based on the minimum number of LED beads that can be lit simultaneously in each row as set by the user and the total number of LED beads in a row of the target screen, the upper limit of the preset number is determined.

[0037] The preset quantity is determined based on the lower limit and the upper limit of the preset quantity.

[0038] Secondly, this application provides a light distribution data calibration device, comprising:

[0039] The test image acquisition module is used to acquire test images of the display device when multiple LEDs are lit, wherein there are unlit LEDs between adjacent lit LEDs.

[0040] The influence value calculation module is used to calculate the influence value of each lit LED on the light distribution of other lit LEDs based on the test brightness of each LED in the test image.

[0041] The light distribution calibration module is used to obtain the light distribution data of each lamp lit by the display device based on the initial light distribution data of each lit lamp read from the test image and the light distribution influence value.

[0042] Thirdly, this application provides an electronic device, including: a processor and a memory, wherein code is stored in the memory, and the processor executes the code stored in the memory to perform the method provided in the first aspect of this application.

[0043] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method provided in the first aspect of this application.

[0044] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method provided in the first aspect of this application.

[0045] The light distribution data calibration method, apparatus, device, storage medium, and program product provided in this application illuminate multiple LEDs of a display device at intervals during each test, and acquire test images of the multiple LEDs illuminated. The test images yield the test brightness and initial light distribution data of each illuminated LED. Using the test brightness read from the test images, the light distribution influence value between the illuminated LEDs is calculated. Then, based on this light distribution influence value and the initial light distribution data of the illuminated LEDs read from the test images, the light distribution data of the illuminated LEDs is obtained. This method calibrates the light distribution data of multiple LEDs simultaneously using test images, improving the efficiency of light distribution data calibration. Furthermore, by utilizing the initial light distribution data read from the test images and the calculated influence of an illuminated LED on surrounding illuminated LEDs, the accuracy of light distribution data calibration is improved. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0047] Figure 1A A schematic diagram of a Mini LED display screen provided for an embodiment of this application;

[0048] Figure 1B A schematic diagram of an LED light distribution provided in an embodiment of this application;

[0049] Figure 2 A schematic flowchart illustrating a light distribution data calibration method provided in an embodiment of this application;

[0050] Figure 3 For this application Figure 2 The diagram shows the distribution of multiple LEDs that were lit during the acquisition of the test image.

[0051] Figure 4 A schematic diagram of the central and non-central regions of the LED bead provided in the embodiments of this application;

[0052] Figure 5 A flowchart illustrating another optical distribution data calibration method provided in this application embodiment;

[0053] Figure 6 This is a schematic diagram of a calibration pipeline provided in an embodiment of this application;

[0054] Figure 7 A schematic diagram illustrating the process of determining the truncated region based on corner detection provided in an embodiment of this application;

[0055] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0056] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0057] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0058] Figure 1AThis is a schematic diagram of a Mini LED display screen provided in an embodiment of this application. Figure 1B This is a schematic diagram of an LED light distribution provided in an embodiment of this application, as shown below. Figure 1A As shown, a Mini LED display screen (also known as a display panel) has a large number of LED beads (or simply LEDs or light beads) arranged in a matrix. Figure 1A In this example, the panel is a rectangle. In some embodiments, it can also be other shapes, such as an octagon.

[0059] With Mini LED technology, the LED beads are smaller, resulting in higher contrast in the image.

[0060] See Figure 1B The light distribution of LED beads has the following characteristics: the brightness is higher in the central area and decreases rapidly outwards.

[0061] In pixel-level compensation algorithms, to improve the accuracy of compensation, it is necessary to reconstruct the backlight based on the light distribution data of the LED chips. Therefore, it is necessary to calibrate and store a large amount of light distribution data of the LED chips on the Mini LED display panel.

[0062] However, due to manufacturing process errors, defects, and the influence of edge reflections, different LED beads have different light distribution characteristics, making it impossible to simply use the light distribution of a single LED bead to represent the light distribution of all LED beads on a Mini LED display panel. Therefore, it is necessary to calibrate the light distribution data of each LED bead on the Mini LED display panel. Typically, this is done by calibrating each LED bead individually, which is inefficient.

[0063] During their research, the inventors of this application discovered that the light distribution data of LED beads exhibits different characteristics in different regions, with the light distribution often showing a linear attenuation trend in non-central areas. Based on this, this application proposes a light distribution data calibration method. First, using the pixel values ​​of multiple LED beads that are periodically lit in a test image, the test brightness and initial light distribution data of the lit LED beads are obtained. Then, the influence value of the lit LED beads on the light distribution of other lit LED beads is calculated using the test brightness. Finally, using this influence value and the initial light distribution data, the light distribution data of the lit LED beads is obtained, thus achieving the calibration of the LED bead's light distribution data. By lighting multiple LED beads simultaneously, parallel calibration of the light distribution data of multiple LED beads is achieved, improving calibration efficiency. Simultaneously, the influence of other lit LED beads is considered during calibration, improving calibration accuracy.

[0064] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0065] Figure 2 This is a flowchart illustrating a method for calibrating optical distribution data according to an embodiment of this application. This method can be executed by an electronic device with corresponding data processing capabilities, such as a calibration device, which can be a computer, server, or other device. Figure 2 As shown, this light distribution data calibration method includes the following steps:

[0066] Step S201: Obtain a test image of the display device when multiple LEDs are lit, wherein there are unlit LEDs between adjacent lit LEDs.

[0067] When different test images are captured from the same display device, multiple LEDs from different groups of the display device are lit up.

[0068] In some embodiments, a preset number of unlit LEDs are spaced between adjacent lit LEDs in each lit instance.

[0069] During display device testing, multiple different LEDs can be lit up at a time. A preset number of unlit LEDs are spaced between adjacent LEDs lit up each time. An image acquisition device, such as a camera, can then capture an image of the display device with multiple LEDs lit up, resulting in a test image of the display device.

[0070] The preset quantity can be a default value, such as 2, 3, 5 or other values, or it can be a configurable parameter. Users can configure the preset quantity based on their needs for testing efficiency. The smaller the preset quantity, the more LEDs in a group are lit each time, the fewer test images are displayed on the device, and the higher the efficiency of light distribution data calibration.

[0071] Each display device corresponds to multiple test images. When different test images are acquired, the number of LEDs lit up on the display device is different. The union of the LEDs lit up in the multiple test images corresponding to the display device is the total number of LEDs on the display device.

[0072] For example, Figure 3 For this application Figure 2 The diagram shows the distribution of multiple LEDs that were lit during the acquisition of the test image, as shown below. Figure 3As shown, assuming the display device includes 30×30 LEDs, with a preset quantity of 9, then when multiple LEDs of the display device are lit for the first time, the 9 LEDs in rows 1, 11, and 21, and columns 1, 11, and 21 respectively can be lit. The lit LEDs are in... Figure 3 The center is filled with gray. During the second illumination, nine LEDs in columns 2, 12, and 22 of rows 1, 11, and 21 are illuminated respectively, and so on, until all LEDs on the display device have been illuminated once. After each illumination of nine LEDs, a test image is captured by a camera.

[0073] In some embodiments, the display device can be placed on a test platform and positioned opposite a camera, so that the camera can capture test images of the display device with multiple LEDs lit.

[0074] Optionally, acquiring test images of the display device when multiple LEDs are lit includes:

[0075] When multiple LED beads on the panel of the display device are lit up in batches, test images of the display device are acquired by an image acquisition device when multiple LED beads are lit up in each batch. The multiple LED beads lit up in different batches are different.

[0076] A display device can correspond to one or more panels. The multiple LEDs of the display device lit in each batch include the multiple LEDs on each panel of the display device. Assuming that the display device includes n1 panels and the number of LEDs lit in each batch is n2, then the number of LEDs lit in each panel in each batch is n2 / n1.

[0077] Optionally, acquire test images of the display device when multiple LEDs are lit, including:

[0078] After the display device is conveyed to the shooting area by the conveyor belt, multiple LED beads on the panel of the display device are lit up in batches, and an image of the display device after the multiple LED beads are lit is captured by the camera above the shooting area to obtain a test image.

[0079] During testing, the display device can be placed on a conveyor belt, which transports the display device to the camera's shooting area. After each batch of multiple LEDs on the display device is lit, the camera located above the shooting area captures an image of the display device, resulting in a test image of the display device.

[0080] Using a conveyor belt to transport display equipment for test image acquisition facilitates batch testing of multiple display devices, enabling assembly line operations and thus calibrating the light distribution data of the LED beads, improving the efficiency and convenience of batch calibration.

[0081] Step S202: Based on the test brightness of each of the plurality of LEDs in the test image, calculate the influence value of each lit LED on the light distribution of the other lit LEDs.

[0082] The test brightness of the LED in the test image can be determined based on the pixel value of the pixel corresponding to the LED in the test image, such as the maximum value, average value or other statistical value of the brightness of the pixel corresponding to the LED.

[0083] After obtaining a test image, the pixel values ​​of each lit LED in the test image are read, such as brightness. Based on the maximum, average, or other statistical values ​​among the read pixel values ​​of the LEDs, the test brightness of the LEDs is obtained. Alternatively, the initial light distribution data of the LEDs can be obtained based on the read pixel values ​​of the lit LEDs.

[0084] The test image can be segmented into LED beads to obtain the test image of each LED bead in the display device. Then, the pixel value of each pixel in the test image of the LED bead can be read to obtain the test brightness and initial light distribution data of the LED bead.

[0085] Optionally, the step of calculating the influence of each lit LED on the light distribution of the other lit LEDs based on the test brightness of each LED in the test image includes:

[0086] For each of the plurality of LEDs, the test brightness of the LED is determined based on the test image; based on the test brightness of the LED and the stored weight matrix, the influence value of the LED on the light distribution of the other lit LEDs is determined.

[0087] For each lit LED, based on its test brightness and the stored weight matrix, the influence of the LED on the light distribution data of other lit LEDs on the same display device is calculated, and the light distribution influence value of the LED on the other lit LEDs is obtained. By traversing through each lit LED, the light distribution influence value among the lit LEDs can be obtained.

[0088] The weight matrix is ​​used to describe the proportional relationship between the light distribution value at each location in the region excluding the central region of the LED and the test brightness of the LED.

[0089] In some embodiments, LEDs at different positions in the same model of display device can correspond to a weight matrix.

[0090] In other embodiments, LEDs at different positions in the same type of display device can each correspond to a weight matrix.

[0091] The weight matrix can be represented as W (m,n), which is used to describe the weight coefficient of the light-emitting diode at the m-th row and n-th column of the display device. The point light distribution value at any position (i, j) in the area except the central area of the light-emitting diode can be expressed as: W (m,n) (i, j) × L (m,n) , where W (m,n) (i, j) represents the element at the i-th row and j-th column of the weight matrix W (m,n) , and L (m,n) represents the measured brightness of the light-emitting diode at the m-th row and n-th of the display device.

[0092] For each light-emitting diode of each model of the display device, the weight matrix of the light-emitting diode can be pre-stored. When the light distribution data of the light-emitting diode is determined, the measured brightness of the light-emitting diode is determined based on the test image, and based on the measured brightness of the light-emitting diode and the stored weight matrix of the light-emitting diode, the influence value of the light distribution of the light-emitting diode on other light-emitting diodes that are lit together in the display device is calculated.

[0093] Step S203: Based on the initial light distribution data of each lit light-emitting diode read from the test image and the light distribution influence value, obtain the light distribution data of each lit light-emitting diode of the display device.

[0094] For each lit light-emitting diode, after calculating the influence value of the light distribution of other light-emitting diodes that are lit together with the light-emitting diode in the same display device on the light distribution of the light-emitting diode, the sum of the influence values of the light distribution of other light-emitting diodes that are lit together with the light-emitting diode on the central area of the light-emitting diode in the same display device is statistically calculated. The light distribution data of the light-emitting diode can be the difference obtained by subtracting the sum of the influence values of the light distribution of other light-emitting diodes that are lit together with the light-emitting diode on the central area of the light-emitting diode from the initial light distribution data of the light-emitting diode.

[0095] The area where the light distribution data of a light-emitting diode is located is divided into a central area and a non-central area. The central area is an area centered on the center of the area where the light distribution data is located, and the non-central area is the remaining area after removing the central area.

[0096] The central area can be a square area, a circular area or an area of other shapes.

[0097] The area where the light distribution data of the light-emitting diode is located can be a square area, such as a square area of A × B. The central area can be a square area of a × b centered on the center of the A × B square area, where a < A and b < B. a and b can be determined based on A and B.

[0098] Exemplarily, a / A = b / B, and a can be 50%, 60%, 75% or other percentages of A.

[0099] Exemplarily, Figure 4A schematic diagram of the central and non-central regions of the LED bead provided in the embodiments of this application is shown below. Figure 4 As shown, assume the light distribution data of the LED bead is located in a 1000×1000 square area, with point O at the center. The central area can be a 600×600 square area centered on point O. The coordinates (x, y) of points within the central area satisfy: 200≤x≤800, 200≤y≤800. The area remaining after removing the central area is the non-central area. The coordinates (x, y) of points within the non-central area satisfy: x<200 or x>800, y<200 or y>800.

[0100] The light distribution data of the central and non-central regions of the same LED chip constitutes the light distribution data of that LED chip. The light distribution data of the central region of the LED chip can be obtained by the methods provided in steps S202 and S203, while the light distribution data of the non-central region of the LED chip can be calculated by the test brightness of the LED chip and the weight matrix of the LED chip.

[0101] After obtaining the light distribution data of the non-central area and the central area of ​​the same LED, the two light distribution data are spliced ​​together according to their location to obtain the complete light distribution data of the LED. The complete light distribution data of the LED is then stored.

[0102] In some embodiments, the light distribution data of the LED chips can be compressed to reduce storage costs. Different compression algorithms can be used to compress the light distribution data of the central region and the non-central region of the LED chips respectively, to obtain compressed light distribution data, which is then stored.

[0103] The light distribution data calibration method provided in this embodiment illuminates multiple LEDs of a display device at intervals during each test, and acquires test images of the LEDs when they are illuminated. The test images yield the test brightness and initial light distribution data of each illuminated LED. Using the test brightness read from the test images, the light distribution influence value between the illuminated LEDs is calculated. Then, based on this influence value and the initial light distribution data of the illuminated LEDs read from the test images, the light distribution data of the illuminated LEDs is obtained. This method calibrates the light distribution data of multiple LEDs simultaneously using test images, improving the efficiency of light distribution data calibration. Furthermore, by utilizing the initial light distribution data read from the test images and the calculated influence of an illuminated LED on surrounding illuminated LEDs, the accuracy of light distribution data calibration is improved.

[0104] In some embodiments, to further improve efficiency, multiple display devices or multiple panels of display devices can be tested at once. For example, multiple panels arranged in a matrix can be conveyed to the shooting area by a conveyor belt each time. These multiple panels can correspond to the same display device or multiple display devices, such as 2×2, 3×2, 3×3 or other arrangements of multiple panels, which can be configured according to the size of the conveyor belt and the size of the display devices.

[0105] Each panel can be placed in a designated area on the conveyor belt. After the camera captures test images of multiple panels, the test images of multiple panels can be evenly divided to obtain the test image of each panel.

[0106] Taking multiple panels arranged in a 2×2 pattern as an example, the test image of the 2×2 panel can be divided into 4 equal parts. The midpoint of the row and column of the test image is used as the dividing point to divide it into 4 images. The resulting images are the test images of each panel in the 2×2 panel.

[0107] Figure 5 This is a flowchart illustrating another optical distribution data calibration method provided in this application embodiment. This embodiment is... Figure 2 Based on the illustrated embodiment, steps S201, S203, and S204 are further defined. To further improve efficiency, in this embodiment, multiple panels are tested simultaneously at a time.

[0108] like Figure 5 As shown, the light distribution data calibration method provided in this embodiment may specifically include the following steps:

[0109] Step S501: Based on the images of each panel of at least one display device when some of the LEDs are lit, determine the cropping area of ​​each panel.

[0110] When determining the cut-off area, the LEDs that are lit on the panel may include LEDs located at the edge of the panel (referred to as edge LEDs). Taking LEDs arranged in a matrix as an example, edge LEDs may include LEDs in the first row, the last row, the first column, and the last column.

[0111] Specifically, some LEDs may include those located at the vertices of the polygon where the LED array corresponding to the panel is located.

[0112] In some embodiments, the portion of the LEDs on the panel that are illuminated when the cut-off area is determined can be all the LEDs on the panel.

[0113] For example, all the LEDs on each panel of the display device can be lit up, and then an image acquisition device, such as a camera, can capture images of multiple panels with all the LEDs lit up to obtain an edge test image. The cropping area of ​​each panel is determined by using the edge test image.

[0114] Specifically, image processing algorithms such as corner detection algorithms and target detection algorithms can be used to determine the cut-off area of ​​each panel through edge test images.

[0115] The conveyor belt can transport multiple panels to the camera's shooting area at a time, so that the image captured by the camera contains images of multiple panels, which can further improve the parallelism of lamp bead light distribution data calibration, thereby improving calibration efficiency.

[0116] The conveyor belt, camera, and subsequent image processing equipment constitute the calibration production line. This line enables the calibration of LED light distribution data on batch display devices.

[0117] For example, Figure 6 This is a schematic diagram of the calibration pipeline provided in the embodiments of this application, such as... Figure 6 As shown, each group on the conveyor belt includes 2×2 panels, which can be panels from the same display device or correspond to multiple display devices, such as corresponding to different display devices. After the conveyor belt transports one group of panels to the camera's shooting area, it sequentially controls the panels in that group to light up multiple LEDs in each batch according to the configured control strategy. The camera then captures images of the panel group after each batch of LEDs is lit, including edge test images and subsequent images to be segmented. The images captured by the camera are sent to a post-processing device, which performs the subsequent steps of this embodiment to calibrate the LED light distribution data. Figure 6 In this context, "panel" refers to a panel.

[0118] For example, when acquiring edge test images, some LEDs can be lit up to their maximum brightness.

[0119] Specifically, the cut-off area of ​​each panel in multiple panels of at least one display device can be determined based on the position of the lit LEDs in the edge test image.

[0120] Taking the edge test image as an example, where all LEDs on the panel are lit, since there is a certain interval between adjacent panels, the edges of each panel in multiple panels can be identified based on the edge detection algorithm, and then the cropping area of ​​each panel can be obtained based on the identified edges.

[0121] The cut-off area can be a rectangular area. For a panel with a rectangular shape, the cut-off area of ​​the panel can be obtained directly by identifying the edges of the panel. If the panel is not rectangular, the bounding rectangle of the polygon formed by the identified edges of the panel can be regarded as the cut-off area of ​​the panel.

[0122] Optionally, some of the LEDs include LEDs at each corner of the panel; based on the edge test image, the cropping area of ​​each panel is determined, including:

[0123] Corner detection is performed on the edge test image to obtain the corner points of each panel; based on the corner points of each panel, the cropping area of ​​each panel is determined.

[0124] Specifically, an image coordinate system can be established with the top left corner of the edge test image as the origin. By performing corner detection on the edge test image, the coordinates of each corner point in the edge test image can be identified.

[0125] Based on the range of coordinates of each corner point, the panel corresponding to each corner point is determined, and then the cut-off area of ​​the panel is obtained based on the coordinates of each corner point of the panel.

[0126] Figure 7 This is a schematic diagram illustrating the process of determining the truncated region based on corner detection provided in an embodiment of this application, as shown below. Figure 7 As shown, assuming the edge test image includes 2×2 panels, namely panels a, b, c, and d, and the image coordinate system XOY is as follows: Figure 7 As shown, the coordinates of the lower right corner of the edge test image are (h, w). Through corner detection, 20 corner points are obtained. Figure 7 Corner points and their coordinates are represented by solid circles. Corner points with x-coordinates less than h / 2 and y-coordinates less than w / 2 are designated as corner points of panel a; corner points with x-coordinates greater than h / 2 and y-coordinates less than w / 2 are designated as corner points of panel b; corner points with x-coordinates less than h / 2 and y-coordinates greater than w / 2 are designated as corner points of panel c; and corner points with x-coordinates greater than h / 2 and y-coordinates greater than w / 2, or any remaining corner points, are designated as corner points of panel d.

[0127] Connecting the corner points of the same panel in a clockwise or counterclockwise order will create a polygon. This polygon can be used directly as the cutoff area of ​​the panel, or its bounding rectangle can be used as the cutoff area. See also... Figure 7 Taking a rectangular cutoff region as an example, the cutoff region of panel b is as follows: Figure 7 The dashed box in the image is shown.

[0128] Step S502: When lighting up multiple LED beads on each panel in batches, the image to be segmented of the at least one display device is acquired by the image acquisition device when multiple LED beads are lit in each batch.

[0129] After obtaining the cut-off area of ​​each panel, for each of the at least one display devices, multiple LEDs of each panel of the display device are lit up in batches. The number of multiple LEDs lit up each time should be as equal as possible. For each panel, there is a preset number of unlit LEDs between every two adjacent LEDs lit up.

[0130] For multiple panels with the same LED arrangement, the LEDs that are lit each time can be multiple LEDs in the same position.

[0131] After lighting up a batch of multiple LEDs in at least one display device, an image is captured by an image acquisition device such as a camera to obtain an image to be segmented.

[0132] Step S503: Obtain the test image of each panel from the image to be segmented by cropping the area of ​​each panel.

[0133] Using the previously obtained cropped regions of each panel, the image to be segmented is segmented, and the test images of each panel are extracted.

[0134] Steps S502 to S503 can be repeated multiple times until each LED on each panel is lit at least once, resulting in multiple test images of each panel, thereby calibrating the light distribution data on a panel-by-pane basis.

[0135] Step S504: For each lit LED bead, based on the test image, determine the test brightness of the LED bead and the initial light distribution data of its central region.

[0136] Step S505: Based on the test brightness of the LED and the stored weight matrix, determine the light distribution data of the non-central region of the LED.

[0137] The light distribution data of the non-central area of ​​the LED can be obtained by multiplying the LED's test brightness by the stored weight matrix of that LED.

[0138] Step S506: For other LEDs lit in the same test image as the LED, based on the LED's test brightness, the stored weight matrix of the LED, and the positional offset of the other LEDs relative to the LED, determine the light distribution influence value of the LED on the central region of the other LEDs.

[0139] For any lit LED, the influence of other LEDs lit at the same time on the light distribution of the central area of ​​that LED can be calculated.

[0140] Other LEDs in the m-th row and n-th column (m,n) The influence value M of light distribution in the central region others(m,n)The following expression can be used to calculate:

[0141]

[0142] Among them, L (x,y) The LED in the x-th row and y-th column is lit. (x,y) LED test brightness (x,y) With LED (m,n) Light up together, (x,y)≠(m,n); offsetv (x,y) and offseth (x,y) For LED (x,y) Compared to LED (m,n) Position offset; W (x,y) (i+offsetv (x,y) ,j+offseth (x,y) This means that in (i+offsetv) (x,y) ,j+offseth (x,y) LED at location (x,y) The weighting coefficients.

[0143] led (x,y) Compared to LED (m,n) Position offset can make LED (m,n) Taking the center of the coordinate system as the origin, we obtain the LED coordinate system. (x,y) The coordinates of the center, i.e., the offset v (x,y) and offseth (x,y) .

[0144] Step S507: Based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead, determine the light distribution data of the central region of the LED bead.

[0145] Optionally, determining the light distribution data of the central region of the LED bead based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead includes:

[0146] The light distribution data of the central region of the LED bead is determined as the difference between the initial light distribution data of the central region of the LED bead and the sum of the influence values ​​of the other LED beads lit on the light distribution of the central region of the LED bead.

[0147] By superimposing the influence values ​​of all other LEDs lit up at the same time and located on the same display device on the light distribution of the central area of ​​the LED, the sum of the light distribution influence values ​​is obtained. The difference between the initial light distribution data of the central area of ​​the LED and the sum of the light distribution influence values ​​is then calculated to obtain the light distribution data of the central area of ​​the LED. That is, the LED. (m,n) Light distribution data of the central area lamp M(m,n) for:

[0148] M (m,n) =I (m,n) -M others(m,n)

[0149] Among them, I (m,n) LED beads (m,n) Initial light distribution data for the central region.

[0150] The light distribution data of the central area and the light distribution data of the non-central area of ​​the same LED bead constitute the complete light distribution data of the LED bead. The complete light distribution data of the LED bead can be stored directly, or the light distribution data can be compressed before storage.

[0151] Optionally, the method further includes:

[0152] The light distribution data of the central region and the non-central region of the same LED bead are compressed to obtain compressed light distribution data; the compressed light distribution data is then stored.

[0153] In some embodiments, only the light distribution data of the central region of the LED chip or the light distribution data of the non-central region can be compressed.

[0154] When compressing the light distribution data of non-central regions, polynomial fitting can be performed on the light distribution data of non-central regions, and the resulting polynomial fitting relationship can be used as the compressed light distribution data of non-central regions.

[0155] When compressing the light distribution data of the central region, singular value decomposition can be performed on the light distribution data of the central region, and the matrix obtained by decomposition can be used as the compressed light distribution data of the central region.

[0156] Other compression algorithms can also be used to compress the light distribution data of the central and / or non-central regions of the LED beads, and this application does not limit this.

[0157] Since display devices contain a large number of LEDs, compressing the light distribution data of these LEDs can greatly reduce storage pressure and lower storage costs.

[0158] In this embodiment, parallel testing of multiple panels is achieved. By pre-illuminating some LEDs in the panel to obtain images, the cropping area of ​​each panel is determined, providing a basis for segmenting the test images of each panel from the images. This realizes a strategy for parallel calibration of LEDs in multiple panels, further improving the parallelism and efficiency of LED calibration. Since multiple LEDs are lit simultaneously, they will interfere with each other. By utilizing the relative positional offset relationship between LEDs, the weight matrix of LEDs, and the test brightness, the influence value between LEDs is accurately calculated. By subtracting the brightness caused by the influence of other LEDs from the initial light distribution data of the central area read from the test image, the true light distribution data of the central area of ​​the LEDs can be obtained, improving the accuracy of the central area light distribution data calibration.

[0159] The weight matrix used in light distribution calibration can be a default value or obtained through testing. That is, before calibrating the light distribution data of display devices or panel LEDs, the weight matrix of each LED in the display device or panel can be obtained by testing sample display devices of the same model.

[0160] Optionally, before acquiring a test image of the display device with multiple LEDs lit, the method further includes:

[0161] Acquire test images from multiple sample display devices when at least one LED is lit, wherein the sample display devices are of the same model as the display device; based on the test images from the sample display devices, determine the test brightness of the lit LED and the light distribution data of the non-central area; based on the test brightness of the lit LED and the light distribution data of the non-central area, determine the weight matrix of the lit LED; and take the average of the weight matrices of the lit LEDs at the same position in the multiple sample display devices as the weight matrix of the LED at that position in the display device.

[0162] Each LED bead in the sample display device can be lit sequentially, and a test image can be captured. Using the captured test image, the test brightness and light distribution data of the non-central area of ​​the LED bead can be read. Based on the test brightness and light distribution data of the non-central area of ​​the LED bead, the weight matrix of the LED bead can be calculated. This weight matrix can be used as the weight matrix of LED beads in the same position of the same model of display device.

[0163] In the weight matrix of the LED bead, each weight coefficient is the ratio of the test brightness of the LED bead to the light distribution value of the corresponding position in the light distribution data of the non-center area of ​​the LED bead.

[0164] To improve the accuracy of the weight matrix, the weight matrix of the LEDs at the same position in multiple sample display devices of the same model can be obtained by averaging the weight matrices of the LEDs at the same position in the same display device.

[0165] To improve the efficiency of determining the weight matrix, multiple LEDs of the sample display device can be lit to obtain a test image of the sample display device. Through the test image, the test brightness and light distribution data of the multiple lit LEDs and the non-central area can be read. The weight matrix of the LED can then be obtained from the test brightness and non-central area light distribution data of the LED.

[0166] In some embodiments, for LEDs lit at the same location in multiple sample display devices, the test brightness and light distribution data of multiple LEDs at that location and the light distribution data of the non-central area can be averaged to obtain the average test brightness and the average light distribution data of the non-central area. Then, the ratio of the average test brightness and the average light distribution data of the non-central area can be calculated to obtain the weight matrix of the LED at that location in the display device. The weight matrix is ​​stored to calibrate the light distribution data of the LED at that location.

[0167] By averaging multiple sample display devices after pre-testing, the weight matrix of the LEDs at each location is obtained, which improves the accuracy of the weight matrix and thus improves the accuracy of light distribution data calibration.

[0168] Before calibrating the light distribution data of the LEDs on the display device, that is, before acquiring test images, it is necessary to first determine the number of unlit LEDs between adjacent LEDs when multiple LEDs are lit on the display device, that is, to determine the preset number of the display device and achieve adaptive setting of the preset number.

[0169] Optionally, the method further includes:

[0170] Based on the size of the central area of ​​the LED beads in the display device and the spacing between adjacent LED beads in the display device, a lower limit value for the preset number is determined; based on the minimum number of LED beads that can be lit simultaneously in each row as set by the user and the total number of LED beads in a row of the display device, an upper limit value for the preset number is determined; based on the lower limit value and the upper limit value for the preset number, the preset number is determined.

[0171] The central area of ​​the LED can be a square or a rectangle. Assuming its minimum side length is D, and the interval between two adjacent LEDs on the display device is set to d, then the lower limit of the preset quantity can be the result of D / d-1 rounded up, that is, the preset quantity is: ceil(D / d-1).

[0172] By setting a preset lower limit, it can be ensured that the central areas of two adjacent LED beads lit up at the same time on the display device do not overlap, thereby simplifying the calculation of the impact of two adjacent LED beads on each other's central areas when lit up.

[0173] You can directly set the preset quantity as its lower limit, or any positive integer greater than or equal to that lower limit.

[0174] To balance calibration efficiency, users can also set the minimum number N of LEDs that can be lit simultaneously in each row. If the total number of LEDs in a row of the display device is n, then the upper limit of the preset number can be the result of n / N-1 rounded up, which is ceil(n / N-1).

[0175] After obtaining the upper and lower limits of the preset quantity, any positive integer within the range of the upper and lower limits can be used as the preset quantity of the display device, so that when acquiring the test image of the display device, a preset number of unlit LEDs are spaced between each set of multiple lit LEDs.

[0176] In this application embodiment, in order to improve efficiency, some serial steps can also be executed in parallel, or in other serial order, provided that they are logically consistent; for some parallel steps, provided that they are logically consistent, this application does not impose any mandatory restrictions on the execution order or the serial-parallel execution method between the steps.

[0177] Compared with the light distribution data calibration method provided in the foregoing embodiments, this application also provides a light distribution data calibration device, including:

[0178] The test image acquisition module is used to acquire a test image of the display device when multiple LEDs are lit, wherein adjacent lit LEDs are spaced apart by unlit LEDs; the influence value calculation module is used to calculate the influence value of each lit LED on the light distribution of other lit LEDs based on the test brightness of each LED in the test image; the light distribution calibration module is used to obtain the light distribution data of each lit LED in the display device based on the initial light distribution data of each lit LED read from the test image and the light distribution influence value.

[0179] Optional, the test image acquisition module is specifically used for:

[0180] When multiple LED beads on the panel of the display device are lit up in batches, test images of the display device are acquired by an image acquisition device when multiple LED beads are lit up in each batch. The multiple LED beads lit up in different batches are different.

[0181] Optional, the test image acquisition module is specifically used for:

[0182] After the display device is conveyed to the shooting area by the conveyor belt, multiple LEDs of the display device are lit up in batches, and the image of the display device after each batch of multiple LEDs is lit is captured by the camera above the shooting area to obtain a test image.

[0183] Optionally, the test image acquisition module includes:

[0184] The cropping area determination unit is used to determine the cropping area of ​​each panel based on the edge test image of each panel of at least one display device when some LEDs are lit; the image to be segmented unit is used to acquire the image to be segmented of the at least one display device when multiple LEDs of each panel are lit in batches through an image acquisition device; the image segmentation unit is used to obtain the test image of each panel from the image to be segmented through the cropping area of ​​each panel.

[0185] Optionally, the interception region determination unit is specifically used for:

[0186] Corner detection is performed on the edge test image to obtain the corner points of each panel; based on the corner points of each panel, the cropping area of ​​each panel is determined.

[0187] Optional, the influence value calculation module is specifically used for:

[0188] For each of the plurality of LEDs, the test brightness of the LED is determined based on the test image; based on the test brightness of the LED and the stored weight matrix, the influence value of the LED on the light distribution of the other lit LEDs is determined.

[0189] Optional, the influence value calculation module is specifically used for:

[0190] For each lit LED, the test brightness of the LED is determined based on the test image; for other lit LEDs located in the same test image as the lit LED, the influence value of the lit LED on the light distribution of the central region of the other LEDs is determined based on the test brightness of the lit LED, the stored weight matrix of the lit LED, and the positional offset of the other LEDs relative to the lit LED.

[0191] Optional, the light distribution calibration module includes:

[0192] An initial data acquisition unit is used to determine the initial light distribution data of the central region of each of the plurality of LEDs based on the test image; a central distribution calibration unit is used to determine the light distribution data of the central region of the LED based on the initial light distribution data of the central region of the LED and the influence values ​​of other lit LEDs on the light distribution of the central region of the LED; and a non-central distribution calibration unit is used to determine the light distribution data of the non-central region of the LED based on the test brightness of the LED and the stored weight matrix of the LED.

[0193] Optional, centrally distributed calibration unit, specifically used for:

[0194] The light distribution data of the central region of the LED bead is determined as the difference between the initial light distribution data of the central region of the LED bead and the sum of the influence values ​​of the other LED beads lit on the light distribution of the central region of the LED bead.

[0195] Optionally, the light distribution data calibration device further includes a weight matrix determination module, used for:

[0196] Before acquiring test images of the display device with multiple LEDs lit, test images of multiple sample display devices with at least one LED lit are acquired, wherein the sample display devices are of the same model as the display device. Based on the test images of the sample display devices, the test brightness of the lit LEDs and the light distribution data of the non-central area are determined. Based on the test brightness of the lit LEDs and the light distribution data of the non-central area, the weight matrix of the lit LEDs is determined. The average value of the weight matrices of the lit LEDs at the same position in the multiple sample display devices is taken as the weight matrix of the LED at that position in the display device.

[0197] Optionally, the light distribution data calibration device further includes a preset quantity determination module, used for:

[0198] Based on the size of the central area of ​​the LED beads in the display device and the spacing between adjacent LED beads in the display device, a lower limit value for the preset number is determined; based on the minimum number of LED beads that can be lit simultaneously in each row as set by the user and the total number of LED beads in a row of the display device, an upper limit value for the preset number is determined; based on the lower limit value and the upper limit value for the preset number, the preset number is determined.

[0199] Optionally, the optical distribution data calibration device also includes a compressed storage module, specifically used for:

[0200] The light distribution data of the central and non-central regions of the same LED bead are compressed to obtain compressed light distribution data; the compressed light distribution data is then stored.

[0201] The light distribution data calibration device provided in this application embodiment can be used to execute the technical solution of the light distribution data calibration method provided in any of the above embodiments of this application. Its implementation principle and technical effect are similar, and will not be described again here.

[0202] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device provided in this embodiment may include: at least one processor 801; and a memory 802 communicatively connected to the at least one processor; wherein the memory 802 stores instructions that can be executed by the at least one processor 801, and the instructions are executed by the at least one processor 801 to cause the electronic device to perform the method as described in any of the above embodiments.

[0203] Optionally, the memory 802 can be either standalone or integrated with the processor 801.

[0204] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the foregoing embodiments, and will not be repeated here.

[0205] This application also provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are executed by a processor, the methods provided in any of the foregoing embodiments can be implemented.

[0206] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method provided in any of the foregoing embodiments.

[0207] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0208] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application.

[0209] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor. The memory may include high-speed memory, and may also include non-volatile memory, such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk, or optical disc, etc.

[0210] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0211] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside within an application-specific integrated circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic device.

[0212] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0213] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0214] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods provided in the various embodiments of this application.

[0215] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0216] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for calibrating light distribution data, characterized in that, include: Acquire a test image of the display device when multiple LEDs are lit, wherein adjacent lit LEDs are spaced apart by unlit LEDs. Based on the test brightness of each of the multiple LEDs in the test image, calculate the influence value of each lit LED on the light distribution of the other lit LEDs; Based on the initial light distribution data of each lit LED bead read from the test image and the light distribution influence value, the light distribution data of each lit LED bead of the display device is obtained.

2. The method according to claim 1, characterized in that, The acquisition of test images of the display device when multiple LEDs are lit includes: When multiple LED beads on the panel of the display device are lit up in batches, test images of the display device are acquired by an image acquisition device when multiple LED beads are lit up in each batch. The multiple LED beads lit up in different batches are different.

3. The method according to claim 2, characterized in that, When lighting up multiple LEDs on each panel of the display device in batches, a test image of the display device is acquired by an image acquisition device when multiple LEDs are lit in each batch, including: Based on the images of each panel of at least one display device when some of the LEDs are lit, determine the cropping area of ​​each panel; When lighting up multiple LED beads on each panel in batches, the image to be segmented of the at least one display device is acquired by an image acquisition device when multiple LED beads are lit in each batch. Test images of each panel are obtained from the image to be segmented by cropping the area of ​​each panel.

4. The method according to claim 1, characterized in that, The calculation of the influence of each lit LED on the light distribution of the other lit LEDs, based on the test brightness of each LED in the test image, includes: For each of the plurality of LED beads, the test brightness of that LED bead is determined based on the test image; Based on the tested brightness of the LED and the stored weight matrix, the influence of the LED on the light distribution of other lit LEDs is determined.

5. The method according to claim 4, characterized in that, The light distribution data of the LED includes light distribution data of the central region and light distribution data of the non-central region, and the range of effect of the light distribution influence value is the central region; The determination of the influence of the LED on the light distribution of other lit LEDs, based on the tested brightness of the LED and the stored weight matrix, includes: For other LEDs lit in the same test image as the LED, the influence value of the LED on the light distribution of the central region of the other LEDs is determined based on the LED's test brightness, the stored weight matrix of the LED, and the positional offset of the other LEDs relative to the LED.

6. The method according to claim 5, characterized in that, The process of obtaining the light distribution data of each illuminated LED in the display device based on the initial light distribution data of each illuminated LED read from the test image and the light distribution influence value includes: For each of the plurality of LED beads, based on the test image, the initial light distribution data of the central region of that LED bead is determined; Based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead, the light distribution data of the central region of the LED bead is determined. Based on the tested brightness of the LED and the stored weight matrix of the LED, the light distribution data of the non-central region of the LED is determined.

7. The method according to claim 6, characterized in that, The determination of the light distribution data of the central region of the LED bead based on the initial light distribution data of the central region of the LED bead and the influence values ​​of other lit LED beads on the light distribution of the central region of the LED bead includes: The light distribution data of the central region of the LED bead is determined as the difference between the initial light distribution data of the central region of the LED bead and the sum of the influence values ​​of the other LED beads lit on the light distribution of the central region of the LED bead.

8. The method according to claim 6, characterized in that, The method further includes: The light distribution data of the central and non-central regions of the LED beads are compressed to obtain compressed light distribution data. Store the compressed light distribution data.

9. The method according to any one of claims 4-8, characterized in that, Before acquiring a test image of the display device with multiple LEDs lit, the method further includes: Acquire test images of multiple sample display devices when at least one LED bead is lit, wherein the sample display devices are of the same model as the display device; Based on the test images of the sample display device, the test brightness of the lit LED beads and the light distribution data of the non-central area are determined; Based on the test brightness of the lit LEDs and the light distribution data of the non-central area, the weight matrix of the lit LEDs is determined. The average value of the weight matrices of the illuminated LEDs at the same position in the multiple sample display devices is used as the weight matrix of the LEDs at that position in the display device.

10. The method according to any one of claims 1-8, characterized in that, The number of unlit LEDs between adjacent lit LEDs is a preset number, and the method further includes: The lower limit of the preset number is determined based on the size of the central area of ​​the LED beads in the display device and the spacing between adjacent LED beads in the display device. The upper limit of the preset number is determined based on the minimum number of LED beads that can be lit simultaneously in each row as set by the user and the total number of LED beads in a row of the display device. The preset quantity is determined based on the lower limit and the upper limit of the preset quantity.

11. A light distribution data calibration device, characterized in that, include: The test image acquisition module is used to acquire test images of the display device when multiple LEDs are lit, wherein there are unlit LEDs between adjacent lit LEDs. The influence value calculation module is used to calculate the influence value of each lit LED on the light distribution of other lit LEDs based on the test brightness of each LED in the test image. The light distribution calibration module is used to obtain the light distribution data of each lamp lit by the display device based on the initial light distribution data of each lit lamp read from the test image and the light distribution influence value.

12. An electronic device, characterized in that, include: A processor and a memory, wherein code is stored in the memory, and the processor executes the code stored in the memory to perform the method as described in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, implement the method as described in any one of claims 1-10.

14. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-10.

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