Micro-LED micro display device driving control method and device

Abstract

The present invention relates to a Micro-LED micro-display device driving control method and device, comprising the following steps: dividing a target pixel area by a preset display image to obtain sub-pixel blocks; performing electroluminescence spectrum analysis on a target micro-display device based on the sub-pixel blocks to obtain a spectral radiation power distribution; performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; performing pulse width modulation on the target micro-display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; using a distributed control architecture to transmit the multi-level grayscale driving waveform to a corresponding target micro-display device to obtain a Micro-LED display image, thereby solving the technical problem of how to efficiently perform electroluminescence spectrum analysis since each pixel point in a Micro-LED array is an independent light source, and adjusting the luminous characteristics of each pixel point accordingly to ensure consistency of image quality.

Description

Technical Field

[0001] The present invention relates to the technical field of Micro-LED micro display devices, and in particular to a Micro-LED micro display device driving control method and device. Background Art

[0002] With the continuous advancement of display technology, Micro-LED microdisplay devices have gradually entered people's field of vision as an emerging display technology. It has the advantages of self-luminescence, high brightness, low energy consumption and long life, and is widely regarded as an important development direction of the next generation of display technology. However, in practical applications, Micro-LED display technology faces a series of challenges, especially in driving control. Traditional display device driving methods are often not directly applicable to Micro-LED because the latter requires more precise current control to achieve ideal brightness and color performance. In addition, since each pixel in the Micro-LED array is an independent light source, how to efficiently perform electroluminescence spectrum analysis and adjust the luminescence characteristics of each pixel accordingly to ensure the consistency of image quality has become an urgent problem to be solved.

[0003] In the current research context, chromaticity calculation and grayscale driving waveform design are crucial to improving the performance of Micro-LED display devices. Previous methods may rely on fixed grayscale settings, which to some extent limits the optimization space for display effects. By introducing spectral radiation power distribution analysis based on sub-pixel blocks, the luminous characteristics of each target micro-display device can be understood in more detail. This refined analysis can help us overcome the difficulty of traditional driving methods in adapting to different luminous characteristics, and at the same time provide the possibility of achieving more accurate color reproduction. However, existing technologies generally lack the ability to conduct comprehensive and real-time analysis of these characteristics, which makes it difficult to achieve the best display effect in practical applications.

[0004] In order to meet the above challenges, a new drive control method for Micro-LED micro-display devices is proposed. This method first divides the target pixel area of ​​the preset display image to obtain a more refined sub-pixel block structure, thereby laying the foundation for subsequent spectral analysis and chromaticity calculation. Then, the obtained spectral radiation power distribution is used to accurately calculate the chromaticity coordinate data, and finally a multi-level grayscale drive waveform is generated based on these data. More importantly, this method uses a distributed control architecture to transmit the drive waveform, so that each Micro-LED micro-display device can receive a driving signal that matches it, thereby improving the efficiency and image quality of the entire display system. In this way, not only the problems existing in the traditional driving method are solved, but also a new path is opened up for the application of Micro-LED display technology. Summary of the invention

[0005] The main purpose of the present invention is to provide a Micro-LED micro display device driving control method and device, which solves the technical problem of how to efficiently perform electroluminescence spectrum analysis and adjust the luminescence characteristics of each pixel accordingly to ensure consistency of image quality, since each pixel in the Micro-LED array is an independent light source.

[0006] To achieve the above object, the present invention provides a method for driving and controlling a Micro-LED micro display device, comprising the following steps: The target pixel area is divided by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices; Based on the sub-pixel block, an electroluminescence spectrum analysis is performed on the target micro-display device to obtain a spectral radiation power distribution; wherein the Micro-LED micro-display device is used as the target micro-display device; Performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; Performing pulse width modulation on the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; The distributed control architecture is used to transmit the multi-level grayscale driving waveform to the corresponding target micro-display device to obtain the Micro-LED display image.

[0007] Furthermore, the step of dividing the target pixel area by a preset display image to obtain sub-pixel blocks includes: Performing brightness feature analysis on a preset display image to obtain a pixel brightness distribution image, and performing boundary extraction on the pixel brightness distribution image to obtain an edge feature map; Performing adaptive threshold segmentation on the edge feature map to obtain a segmented boundary map; Performing a region growing operation on the target pixel region based on the segmented boundary map to obtain an initial sub-pixel region; A spatial clustering analysis is performed on the initial sub-pixel region to obtain a clustered sub-pixel block, and a center of gravity is located on the clustered sub-pixel block to obtain a located sub-pixel block.

[0008] Furthermore, the electroluminescence spectrum analysis of the target micro display device based on the sub-pixel block to obtain the spectral radiation power distribution includes: Calculating the spectral energy density of the target micro display device based on the sub-pixel block to obtain spectral energy density data; Performing spectral power density analysis based on the spectral energy density data to obtain a power density curve, and performing radiation power efficiency calculation on a target micro-display device based on the power density curve to obtain a radiation power efficiency graph; Calculating the radiation flux density of the radiation power efficiency diagram by a spectral integration operation method to obtain a radiation flux density distribution diagram; The spectral radiation characteristic of the target micro display device is analyzed based on the radiation flux density distribution diagram to obtain the spectral radiation power distribution.

[0009] Furthermore, the chromaticity calculation of the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data includes: Dividing the spectral radiation power distribution into wavelength intervals to obtain wavelength segmentation data, and performing a spectral flux integration operation on the target micro-display device based on the wavelength segmentation data to obtain an integrated spectral flux diagram; Performing chromaticity mapping on the integrated spectral flux diagram by tristimulus value conversion technology to obtain a chromaticity mapping matrix, and normalizing the chromaticity coefficients of the chromaticity mapping matrix to obtain normalized chromaticity coefficients; Performing chromaticity space transformation on the target micro-display device based on the normalized chromaticity coefficient to obtain chromaticity space data; Performing color gamut boundary calculation on the chromaticity space data to obtain a color gamut boundary curve, and performing color purity analysis on the target micro-display device based on the color gamut boundary curve to obtain a color purity distribution diagram; wherein the color purity distribution diagram includes a color gamut range, boundary point coordinates, and color purity values; The color purity distribution diagram is coordinate mapped by a preset chromaticity coordinate conversion technology to obtain a chromaticity coordinate mapping diagram, and chromaticity coordinate data is determined based on the chromaticity coordinate mapping diagram.

[0010] Furthermore, the pulse width modulation of the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform includes: Performing quantization frequency division processing on the chromaticity coordinate data to obtain quantized frequency data, and performing multi-cycle decomposition on the target micro-display device based on the quantized frequency data to obtain cycle decomposition data; wherein the cycle decomposition data includes a pulse frequency parameter, a cycle length parameter and a decomposition coefficient; Performing timing modulation calculation on the target micro display device based on the period decomposition data to obtain a modulation timing sequence, and performing sub-period expansion on the modulation timing sequence to obtain a sub-period modulation diagram; Performing pulse stretching processing based on the sub-period modulation diagram to obtain a stretch modulation spectrum, and performing light emission timing planning on a target micro-display device based on the stretch modulation spectrum to obtain timing planning data; Performing pulse phase alignment on the timing planning data to obtain a phase alignment sequence, and synthesizing a driving waveform on a target micro display device based on the phase alignment sequence to obtain waveform synthesis data; The waveform synthesis data is subjected to multiple modulation superposition to obtain a superimposed driving waveform, and the superimposed driving waveform is subjected to grayscale division through dynamic threshold screening to obtain a multi-level grayscale driving waveform.

[0011] Furthermore, the sub-period expansion of the modulation timing sequence to obtain a sub-period modulation diagram includes: Extracting timing reference points from the modulation timing sequence to obtain a timing reference point set, and dividing the target micro-display device into sub-periods based on the timing reference point set to obtain a sub-period sequence; Calculating the duty cycle of the target micro-display device based on the sub-period sequence to obtain duty cycle data, and performing pulse density modulation on the duty cycle data to obtain a pulse density distribution diagram; Extending the pulse density distribution diagram on a time axis to obtain an extended pulse diagram, and performing waveform interpolation calculation based on the extended pulse diagram to obtain interpolation waveform data; Performing sub-period mapping on the interpolation waveform data to obtain a sub-period waveform diagram, and performing multi-level grayscale encoding on the target micro-display device based on the sub-period waveform diagram to obtain an encoded sub-period waveform diagram; The encoded sub-period waveform diagram is subjected to sub-period fusion through time sequence splicing to obtain a sub-period modulation diagram.

[0012] Furthermore, the method of using a distributed control architecture to transmit a multi-level grayscale driving waveform to a corresponding target micro-display device to obtain a Micro-LED display image includes: Performing time division multiplexing encoding on the multi-level grayscale driving waveform to obtain waveform encoding data, and performing timing synchronization calculation on the target micro display device based on the waveform encoding data to obtain a synchronization timing matrix; Based on the synchronous timing matrix, driving signals of the target micro display device are grouped to obtain grouped driving data, and parallel tasks are assigned to the grouped driving data to obtain a task assignment sequence; Performing node topology construction on the task allocation sequence to obtain a control node topology map, and distributing data streams to the target micro-display device based on the control node topology map to obtain a distribution routing table; Performing concurrent control scheduling on the target micro-display device based on the distribution routing table to obtain a concurrent scheduling scheme, and performing clock synchronization coordination on the concurrent scheduling scheme to obtain a synchronous control instruction sequence; Distributing a driving signal to a target micro display device based on the synchronous control instruction sequence to obtain distribution control data; The distributed control architecture is used to transmit the distribution control data to the corresponding target micro-display device to obtain a Micro-LED display image.

[0013] The present invention also provides a Micro-LED micro display device drive control device, comprising: A division module, used for dividing a target pixel area by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices; An analysis module, used for performing electroluminescence spectrum analysis on a target micro display device based on the sub-pixel block to obtain a spectrum radiation power distribution; wherein the Micro-LED micro display device is used as the target micro display device; A calculation module, used to perform chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; A modulation module, used for performing pulse width modulation on a target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; The transmission module is used to transmit the multi-level grayscale driving waveform to the corresponding target micro-display device using a distributed control architecture to obtain a Micro-LED display image.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0016] The driving control method of the Micro-LED micro-display device provided by the present invention comprises the following steps: dividing the target pixel area by a preset display image to obtain sub-pixel blocks; performing electroluminescence spectrum analysis on the target micro-display device based on the sub-pixel blocks to obtain spectral radiation power distribution; performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; performing pulse width modulation on the target micro-display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; using a distributed control architecture to transmit the multi-level grayscale driving waveform to the corresponding target micro-display device to obtain a Micro-LED display image, solving the technical problem of how to efficiently perform electroluminescence spectrum analysis and adjust the luminous characteristics of each pixel to ensure the consistency of image quality because each pixel point in the Micro-LED array is an independent light source, and realizing that through pulse width modulation based on chromaticity coordinate data, the method can generate a multi-level grayscale driving waveform to provide precise brightness control for each Micro-LED micro-display device. This detailed grayscale control capability enables the display to maintain good contrast and detail level under different brightness conditions, thereby improving the technical effect of the overall visual experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 1 is a schematic diagram of the steps of a method for driving and controlling a Micro-LED micro display device in one embodiment of the present invention; Figure 2 This is a structural block diagram of a Micro-LED micro display device driving control device in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention 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 invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of a method for driving and controlling a Micro-LED micro display device in one embodiment of the present invention; In one embodiment of the present invention, a method for driving and controlling a Micro-LED micro display device is provided, comprising the following steps: Step S1, dividing a target pixel area by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices.

[0021] Specifically, when implementing the above-mentioned steps, it is crucial to divide the target pixel area by a preset display image to obtain sub-pixel blocks. The target pixel area here refers to a specific part on the display device that is actually responsible for presenting the image content, and a number of target micro-display devices, namely Micro-LED micro-display devices, are arranged in the area. These devices are the basic light-emitting units that constitute the display panel, and each of them can emit light independently after receiving an appropriate electrical signal. When a specific image needs to be processed and displayed, the system will first subdivide the entire target pixel area into smaller, manageable parts, namely sub-pixel blocks, according to the content and structural characteristics of the image. This division method is not random, but is determined based on the preset display image to ensure that each sub-pixel block can represent a specific detail or feature in the original image. For example, in the application scenario of high-definition television, if a landscape documentary is to be played, the vast blue sky part in the picture may be divided into larger sub-pixel blocks because the color and brightness changes in this area are relatively uniform; while for the complex and changeable forest trees in the foreground of the picture, a finer division may be used to capture more detail information, thereby ensuring the realism and delicacy of the final display effect. Such a design not only helps to improve the quality of the image, but also lays the foundation for subsequent electroluminescence spectrum analysis, chromaticity calculation and other steps. By reasonably dividing the target pixel area, the spectral characteristics within each sub-pixel block can be made more consistent, thereby simplifying the subsequent analysis process and improving the accuracy of the calculation results. At the same time, this also means that when generating multi-level grayscale driving waveforms, the luminous behavior of each Micro-LED micro-display device can be more accurately controlled to ensure that they work together to present a visual effect that is closest to the original image. In short, this step is an important bridge between the input image data and the physical display device, which directly affects the performance of the entire display system.

[0022] Step S2, performing electroluminescence spectrum analysis on the target micro display device based on the sub-pixel block to obtain spectral radiation power distribution; wherein the Micro-LED micro display device is used as the target micro display device.

[0023] Specifically, when implementing the above-mentioned steps, the process of performing electroluminescence spectrum analysis on the target micro-display device based on the sub-pixel block is a key link to ensure the display quality. The target micro-display devices here specifically refer to Micro-LED micro-display devices, which constitute the basic light-emitting units of the display panel. When these devices receive electrical signals, they will emit light within a specific wavelength range, and electroluminescence spectrum analysis is to measure and record this luminescence characteristic. Specifically, after completing the division of the target pixel area and obtaining the sub-pixel blocks, the next thing to do is to perform a detailed spectral radiation power distribution analysis on the Micro-LED micro-display devices in each sub-pixel block. This process involves using a specially designed spectrometer or other precision instrument to capture the light emitted from each target micro-display device and perform spectral decomposition on it. In this way, the light intensity distribution at different wavelengths, the so-called spectral radiation power distribution, can be accurately measured. This step is crucial to understanding the actual luminous performance of each Micro-LED device, because even small changes may significantly affect the quality of the final image. For example, in the application scenario of high-definition television, suppose we are dealing with a picture of a blue sky that contains subtle changes in multiple blue tones. By analyzing the electroluminescent spectra of the Micro-LED devices in the sub-pixel blocks corresponding to this area, we can know which devices can more accurately reproduce the different shades of blue in the sky. This not only helps to improve the accuracy of color, but also enhances the realism of the picture. For example, when the picture switches to the details of the forest trees, because this part of the image contains a lot of green and other natural colors, through spectral analysis, we can ensure that each color can be presented in the closest way to the real state, thus providing the audience with a more vivid and realistic visual experience. In addition, this meticulous spectral analysis also provides a solid data foundation for subsequent chromaticity calculations. By understanding the specific luminous characteristics of each Micro-LED device, the system can more accurately adjust the luminous behavior of each device in the subsequent steps to achieve the best grayscale performance and color reproduction effect. Therefore, this analysis step is not only an important bridge between physical devices and ideal images, but also an indispensable part of the entire display control system, which directly determines the quality and perception of the final displayed image.

[0024] Step S3, performing chromaticity calculation on the target micro display device based on the spectral radiation power distribution to obtain chromaticity coordinate data.

[0025] Specifically, when implementing the above-mentioned steps, the process of calculating the chromaticity of the target micro-display device based on the spectral radiant power distribution is the key to ensuring the accuracy and consistency of the image color. The target micro-display device here refers to the Micro-LED micro-display device, which constitutes the basic light-emitting unit of the display panel. After the previous electroluminescent spectrum analysis, we have obtained the spectral radiant power distribution data of the Micro-LED device in each sub-pixel block, which provides the basis for the subsequent chromaticity calculation. After having these detailed spectral information, the next thing to do is to use the principles and formulas of colorimetry to calculate the chromaticity coordinate data corresponding to the light emitted by each Micro-LED device. Chromaticity coordinates are a set of values ​​that represent the position of the color on the chromaticity diagram, which can describe the purity (saturation) and hue of the color. By converting the spectral radiant power distribution into chromaticity coordinate data, we can quantify and compare the differences in the luminous characteristics between different Micro-LED devices, and then evaluate whether their color performance when displaying images is in line with expectations. For example, in the application scenario of a landscape documentary played on a high-definition television, when we process the blue sky part of the picture, by performing chromaticity calculations on the Micro-LED devices in the corresponding sub-pixel blocks in this area, we can determine which devices can most accurately reproduce the blue hue in the sky. Assuming that some Micro-LED devices have slightly different luminous characteristics due to subtle differences in the manufacturing process, these differences can be identified through chromaticity calculations, and the driving parameters can be adjusted accordingly so that all related devices can uniformly output the ideal blue, ensuring the color consistency of the entire picture. Similarly, for the details of forest trees, although this part of the image contains a lot of green and other natural colors, through accurate chromaticity calculations, the system can ensure that each color can be presented in the closest way to the real state, thereby providing viewers with a more vivid and realistic visual experience. In addition, this chromaticity calculation based on spectral radiant power distribution also provides an important basis for subsequent pulse width modulation (PWM). By understanding the specific luminous characteristics and chromaticity coordinates of each Micro-LED device, the system can more accurately control the brightness and color of each device when generating multi-level grayscale drive waveforms to achieve the best display effect. Therefore, this colorimetric calculation step not only connects spectral analysis with grayscale control, but is also an integral part of achieving high-quality image display, as it directly determines the accuracy and consistency of the final image color.

[0026] Step S4, performing pulse width modulation on the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform.

[0027] Specifically, when implementing the above-mentioned steps, pulse width modulation (PWM) of the target micro-display device based on the chromaticity coordinate data is a key link to ensure that the Micro-LED micro-display device can accurately reproduce the grayscale and color of the image. This process is based on the previously obtained spectral radiation power distribution and the chromaticity coordinate data calculated therefrom. This information can accurately control the luminous behavior of each Micro-LED device to generate a multi-level grayscale drive waveform. After having the chromaticity coordinate data of each Micro-LED device, the next thing to do is to use this data to adjust the PWM parameters to achieve fine control of the brightness and color of each device. PWM is a common technology that adjusts the average power output to the Micro-LED device by changing the duty cycle of the pulse signal, thereby controlling its luminous intensity. In this process, the system calculates the most suitable PWM duty cycle setting based on the required chromaticity coordinates, so that each Micro-LED device can maintain ideal color performance at different brightness levels. For example, in the application scenario of a landscape documentary played on a high-definition TV, when we process the blue sky part of the picture, because the color and brightness of the sky change more evenly, the system can determine the appropriate PWM parameters by analyzing the chromaticity coordinate data of the Micro-LED devices in the corresponding sub-pixel block to ensure that all relevant blue Micro-LED devices can consistently present the blue closest to the natural state. This not only improves the overall consistency of the picture, but also enhances the audience's visual experience. Similarly, for the details of forest trees, this part of the image contains rich green and other natural tones. Through precise PWM modulation, each Micro-LED device can accurately reproduce the corresponding color according to the preset chromaticity coordinates, and the authenticity and delicacy of the color can be guaranteed even under low brightness conditions. In addition, by combining chromaticity coordinate data with PWM, the color deviation problem existing in traditional display technology can also be effectively solved. Because the actual luminous characteristics of each Micro-LED device may vary slightly due to manufacturing differences, it is difficult to ensure that the luminous effect of all devices is completely consistent by directly using fixed PWM settings. However, by introducing PWM modulation based on chromaticity coordinates, the driving waveform can be dynamically adjusted according to the specific situation of each device to ensure that the color and brightness on the entire display panel are optimally matched. This method not only improves the image quality, but also makes it possible to achieve a higher level of grayscale control, so that the display can maintain good contrast and detail levels under different brightness conditions, thus meeting users' expectations for high-quality display effects. In short, the PWM modulation step based on chromaticity coordinate data is a bridge between color analysis and actual display effects. It ensures that each Micro-LED micro-display device can accurately adjust the luminous characteristics according to the requirements of the image content, and finally work together to present the visual effect closest to the original image.This step is critical to improving the performance of display systems and is an integral part of achieving high-resolution, high-quality image display.

[0028] Step S5, using a distributed control architecture to transmit the multi-level grayscale driving waveform to the corresponding target micro display device to obtain a Micro-LED display image.

[0029] Specifically, when implementing the above-mentioned steps, using a distributed control architecture to transmit the multi-level grayscale drive waveform to the corresponding target micro-display device is a key link to ensure the quality of the Micro-LED display image. This process depends on the results of all previous steps, including the division of the target pixel area, electroluminescence spectrum analysis, chromaticity calculation, and pulse width modulation (PWM) based on chromaticity coordinate data. Through these steps, we have generated accurate multi-level grayscale drive waveforms for each Micro-LED micro-display device. The next task is how to efficiently and accurately transmit these drive signals to the corresponding device. The design of the distributed control architecture is a solution proposed to meet this demand. This architecture allows multiple controllers or nodes to work together in the network, and each node is responsible for processing and transmitting the drive waveform information of the Micro-LED device in a specific area. Compared with a centralized control system, distributed control has higher flexibility and scalability. It can better adapt to complex display panel layouts and reduce signal transmission delays, thereby ensuring the consistency and real-time performance of image display. For example, in the application scenario of a high-definition television playing a landscape documentary, when the system needs to show a vast blue sky or a detailed forest scene, the distributed control architecture can ensure that the Micro-LED devices in each sub-pixel block can receive the driving waveform that matches it, and maintain high consistency of color and brightness even on large-scale display panels. Specifically, the workflow of the distributed control architecture is as follows: First, the system determines which controllers should be responsible for which areas of Micro-LED devices based on a pre-set algorithm. Then, each controller receives an instruction from the central processing unit, which contains the multi-level grayscale driving waveform data in the corresponding area. Then, the controller performs necessary conversion and optimization on this data to adapt to the requirements of the local network environment. Finally, the controller sends the optimized driving waveform to the corresponding Micro-LED devices through a high-speed interface to ensure that they emit light in the expected manner. This design not only improves the system's response speed, but also enhances its fault tolerance, because in the event of a controller failure, other controllers can continue to work normally without affecting the overall display effect. In addition, the distributed control architecture can also support higher-level functions such as dynamic adjustment and personalized calibration. For example, for Micro-LED devices with different batches or individual differences, the system can monitor their luminous characteristics in real time through a distributed control architecture, and adjust the driving waveform accordingly to compensate for possible deviations in the manufacturing process. This helps ensure consistency between all display devices, which is particularly important for mass production and high-end display applications. At the same time, this approach also allows the display to maintain good contrast and detail levels under different brightness conditions, thereby meeting users' expectations for high-quality display effects.In short, the step of using a distributed control architecture to transmit multi-level grayscale drive waveforms to the corresponding target micro-display device is not only a bridge between the drive signal generation and the actual display effect, but also an indispensable part of achieving high-resolution and high-quality image display. In this way, not only can the performance of the display system be improved, but also a more realistic and delicate visual experience can be provided to users.

[0030] In a specific embodiment, dividing the target pixel area by a preset display image to obtain sub-pixel blocks includes: Performing brightness feature analysis on a preset display image to obtain a pixel brightness distribution image, and performing boundary extraction on the pixel brightness distribution image to obtain an edge feature map; Performing adaptive threshold segmentation on the edge feature map to obtain a segmented boundary map; Performing a region growing operation on the target pixel region based on the segmented boundary map to obtain an initial sub-pixel region; A spatial clustering analysis is performed on the initial sub-pixel region to obtain a clustered sub-pixel block, and a center of gravity is located on the clustered sub-pixel block to obtain a located sub-pixel block.

[0031] Specifically, when implementing the above-mentioned steps, the process of dividing the target pixel area by the preset display image to obtain the sub-pixel block is a complex and delicate operation. This process not only involves the application of image processing technology, but also combines geometric analysis and statistical methods to ensure that each sub-pixel block can accurately reflect the details and features in the original image. Specifically, it is necessary to first analyze the brightness characteristics of the preset display image to obtain a pixel brightness distribution image. This step is the basis of the entire division process. It measures and records the brightness value of each pixel in the image to generate a map that can intuitively show the brightness change of the image. Next, based on this pixel brightness distribution image, the system will further perform a boundary extraction operation to obtain an edge feature map. The edge feature map is an important tool for identifying the boundaries between different objects or regions in the image. In the application scenario of high-definition television playing landscape documentaries, for example, when the junction of blue sky and white clouds, forest and sky appears in the picture, boundary extraction can help us clearly distinguish these different elements. In order to improve the accuracy of boundary extraction, the system may use a variety of algorithms and techniques, such as Sobel operator, Canny edge detection, etc., to ensure that the final edge feature map is both complete and accurate. Once the edge feature map is obtained, the next step is to perform adaptive threshold segmentation on it to obtain a segmented boundary map. Adaptive threshold segmentation is a technique that dynamically adjusts the threshold based on local image characteristics. It can effectively deal with the problem of uneven lighting in the image and make boundary recognition more reliable. In this process, the system automatically determines the appropriate threshold based on the brightness distribution of different regions to divide the image into two parts: foreground (i.e., boundary) and background. For the images of landscape documentaries, this means that even in a complex lighting environment, such as the mottled light and shadow formed by sunlight shining through leaves, the system can accurately capture important boundary information such as the outline of trees. With the segmented boundary map, you can start to perform region growing operations on the target pixel area based on it. Region growing is an image segmentation method based on seed point selection. Starting from a selected starting point, it gradually merges adjacent pixels with similar attributes into the same region until all pixels that meet the conditions are included. In this way, a series of initial sub-pixel regions can be obtained, each of which represents a specific object or feature in the image. For example, when processing a picture of a green meadow, the region growing operation can help us distinguish different parts of the meadow into independent but interrelated sub-regions. However, the initial sub-pixel regions obtained by region growing alone may not be ideal, because they may overlap or have irregular shapes. Therefore, it is necessary to perform spatial clustering analysis on these initial sub-pixel regions to obtain more regular and reasonable clustered sub-pixel blocks.Spatial clustering analysis aims to merge the sub-regions into several larger clusters with high internal consistency based on the spatial position relationship and similarity measurement between them. This analysis method can significantly improve the spatial layout of the sub-pixel block, making it better adapted to the needs of subsequent processing. The last step is to locate the center of gravity of the clustered sub-pixel block to obtain the final located sub-pixel block. Center of gravity positioning refers to calculating the geometric center coordinates of each clustered sub-pixel block as the reference point of the block in the entire image. This is crucial to ensure that each Micro-LED micro-display device can be accurately positioned when displaying an image, especially when dealing with complex and changing natural scenes, such as the interlaced branches and leaves of forest trees and the winding rivers. Through accurate center of gravity positioning, each light-emitting unit on the display can be correctly corresponded to the corresponding position in the image, thereby presenting the visual effect closest to the original image. In summary, the above steps constitute a complete process from the preset display image to the target pixel area division, which not only integrates a variety of advanced image processing technologies and algorithms, but also fully considers the needs and challenges of actual application scenarios. Through such detailed division, not only can the image quality be improved, but it can also provide a solid data foundation for subsequent electroluminescence spectrum analysis, colorimetry calculation and other steps, ultimately achieving high-quality, high-resolution Micro-LED display effects.

[0032] In a specific embodiment, the step of performing electroluminescence spectrum analysis on the target micro display device based on the sub-pixel block to obtain the spectral radiation power distribution includes: Calculating the spectral energy density of the target micro display device based on the sub-pixel block to obtain spectral energy density data; Performing spectral power density analysis based on the spectral energy density data to obtain a power density curve, and performing radiation power efficiency calculation on a target micro-display device based on the power density curve to obtain a radiation power efficiency graph; Calculating the radiation flux density of the radiation power efficiency diagram by a spectral integration operation method to obtain a radiation flux density distribution diagram; The spectral radiation characteristic of the target micro display device is analyzed based on the radiation flux density distribution diagram to obtain the spectral radiation power distribution.

[0033] Specifically, in the process of electroluminescence spectrum analysis of the target micro-display device, the step first needs to calculate the spectral energy density based on the sub-pixel block, which is crucial to understanding how each sub-pixel block affects the overall display effect. Specifically, once we have the above-mentioned positioned sub-pixel blocks, we can further study the spectral characteristics generated by these sub-pixel blocks when they emit light. For example, in the application scenario of high-definition television playing landscape documentaries, each Micro-LED micro-display device is equivalent to an independent light source. When they are activated, they will emit light within a specific wavelength range. Therefore, by measuring and calculating the energy distribution of the light emitted by these sub-pixel blocks, we can obtain spectral energy density data. This process not only reveals the luminous intensity of each sub-pixel block, but also shows the characteristics of their energy distribution in the entire visible spectrum. Next, using the obtained spectral energy density data, the system will perform spectral power density analysis on the target micro-display device to generate a power density curve. The power density curve is an important chart used to depict the trend of spectral power density changes corresponding to different wavelengths. It reflects the amount of light power emitted per unit area at each wavelength, which is of key significance for evaluating the performance of micro-display devices. Continuing with the landscape documentary as an example, when we focus on a picture of a blue sky, through spectral power density analysis, we can find that the spectral power density of the blue band is relatively high, which means that the Micro-LED micro-display device in this area has a strong luminous ability within this wavelength range. Subsequently, based on this power density curve, the radiation power efficiency of the target micro-display device can also be calculated, and finally the radiation power efficiency diagram is obtained. Radiative power efficiency refers to the ability of a device to convert input electrical energy into effective light output, which is an important indicator for measuring the energy efficiency ratio of a display. High radiation power efficiency means that less electricity can be consumed while achieving the same brightness level, which is very beneficial for improving the energy efficiency of display devices. In addition, in order to have a more comprehensive understanding of the luminous characteristics of the target micro-display device, it is also necessary to use a spectral integration operation method to process the radiation power efficiency diagram, and then obtain a radiation flux density distribution diagram. Radiative flux density refers to the radiation energy passing through a unit area per unit time, which is directly related to the image brightness and color saturation perceived by the audience. In practical applications, such as when users look at green vegetation in a forest, the radiation flux density distribution map can help engineers optimize the design parameters of Micro-LED micro-display devices to ensure that each sub-pixel block can accurately reproduce the rich color levels of nature. Through precise control of the radiation flux density, the display can be made more realistic and vivid. Finally, based on the obtained radiation flux density distribution map, the system will further analyze the spectral radiation characteristics of the target micro-display device to determine the spectral radiation power distribution.This analysis process takes into account the results of all the previous steps and aims to comprehensively evaluate the performance of microdisplay devices under different working conditions. For example, when simulating the light and shadow effects formed by sunlight shining through the gaps between leaves, the spectral radiant power distribution can help identify which wavelengths of light are most likely to pass through the leaves and reach the audience's eyes, thereby guiding designers to adjust the device's luminous characteristics so that the final image is both in line with natural laws and has good visual impact. In summary, through the detailed analysis of sub-pixel blocks and in-depth discussion of a series of spectral-related characteristics, we can not only gain a deep understanding of the working principles of the target microdisplay device, but also provide valuable data support for future research and development, and promote the development of display technology towards higher quality.

[0034] In a specific embodiment, the chromaticity calculation of the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data includes: Dividing the spectral radiation power distribution into wavelength intervals to obtain wavelength segmentation data, and performing a spectral flux integration operation on the target micro-display device based on the wavelength segmentation data to obtain an integrated spectral flux diagram; Performing chromaticity mapping on the integrated spectral flux diagram by tristimulus value conversion technology to obtain a chromaticity mapping matrix, and normalizing the chromaticity coefficients of the chromaticity mapping matrix to obtain normalized chromaticity coefficients; Performing chromaticity space transformation on the target micro-display device based on the normalized chromaticity coefficient to obtain chromaticity space data; Performing color gamut boundary calculation on the chromaticity space data to obtain a color gamut boundary curve, and performing color purity analysis on the target micro-display device based on the color gamut boundary curve to obtain a color purity distribution diagram; wherein the color purity distribution diagram includes a color gamut range, boundary point coordinates, and color purity values; The color purity distribution diagram is coordinate mapped by a preset chromaticity coordinate conversion technology to obtain a chromaticity coordinate mapping diagram, and chromaticity coordinate data is determined based on the chromaticity coordinate mapping diagram.

[0035] Specifically, when implementing the above-mentioned steps, the process of calculating the chromaticity of the target micro-display device based on the spectral radiant power distribution is a complex and delicate operation, which involves a series of conversions from spectral characteristics to color performance. This process not only ensures that each Micro-LED micro-display device can accurately reproduce the color of the image, but also provides important data support for subsequent pulse width modulation (PWM) to optimize the display effect. First, the spectral radiant power distribution needs to be divided into wavelength intervals to obtain wavelength segmentation data. This step is intended to discretize continuous spectral information for subsequent processing. By selecting a suitable wavelength interval, we can divide the entire visible spectrum into several smaller parts, each of which represents the change in spectral energy within a certain range. For example, in the application scenario of a high-definition television playing a landscape documentary, when different color elements such as blue sky, white clouds and green vegetation appear in the picture, the system divides the spectral interval according to the typical wavelength range corresponding to these colors. Next, based on these wavelength segmentation data, the target micro-display device is subjected to a spectral flux integration operation in order to calculate the total luminous flux emitted in each wavelength interval, thereby obtaining an integrated spectral flux diagram. The integral spectral flux diagram intuitively shows the contribution of luminous flux in each wavelength interval, which is crucial to understanding the actual luminous characteristics of each Micro-LED device. With the integral spectral flux diagram, the system will use the tristimulus value conversion technology to perform chromaticity mapping on it and generate a chromaticity mapping matrix. Tristimulus value conversion is a standard method for converting spectral data into color coordinates that match human visual perception. In this process, the system maps each wavelength segment data in the integral spectral flux diagram to the stimulus values ​​of the three basic colors of red, green, and blue according to CIE1931 or similar standard colorimetric systems. For the images of landscape documentaries, this means that natural colors such as the blue of the sky and the green of the grass can be accurately converted into corresponding tristimulus value combinations. Subsequently, by normalizing the chromaticity coefficients of the chromaticity mapping matrix, we can obtain the normalized chromaticity coefficients. The normalization operation is to eliminate the influence of the difference in the intensity of different light sources so that all colors can be compared and analyzed under a unified standard. The normalized chromaticity coefficients are more stable and reliable, laying the foundation for the next step of chromaticity space transformation. Next, the target micro-display device is transformed into a chromaticity space based on the normalized chromaticity coefficient to obtain chromaticity space data. Chromaticity space transformation is the conversion of the original color data into a specific chromaticity space, such as CIELAB or CIEXYZ. These chromaticity spaces have better linearity and uniformity, and can better reflect the characteristics of the human visual system. Continuing with the landscape documentary as an example, when we want to ensure that the colors of the forest trees in the picture are both bright and natural, through chromaticity space transformation, the light-emitting parameters of each Micro-LED device can be adjusted more accurately, so that the final green presented is closer to the real world.In addition, the color space data can also help us identify and quantify the subtle differences between different colors, which is very important for improving the overall quality of the image. Then, the color space data is subjected to color gamut boundary calculation to obtain the color gamut boundary curve, and based on this, the target micro display device is subjected to color purity analysis to obtain a color purity distribution map. The color gamut boundary curve defines the limit of the range of all colors that a device can reproduce, while color purity refers to the saturation or purity of the color. Through the color gamut boundary calculation, the color range that the display can cover can be determined and its color performance can be evaluated accordingly. For example, when showing a blue sky, the color gamut boundary curve can help us determine whether the display can fully reproduce the various shades of blue in the sky. At the same time, color purity analysis focuses on the purity of each specific color point, that is, the degree to which they deviate from grayscale. The color purity distribution map includes not only the color gamut range and boundary point coordinates, but also the specific color purity value of each color point, which is critical to ensure that all colors in the image achieve the ideal visual effect. Finally, the color purity distribution diagram is mapped by the preset chromaticity coordinate conversion technology to obtain the chromaticity coordinate mapping diagram, and the final chromaticity coordinate data is determined based on this. Chromaticity coordinate conversion is to convert color information from one chromaticity space to another more intuitive or applicable space, such as the CIE 1931 xy chromaticity diagram. Through such a conversion, we can more easily understand and operate color data, and it also provides convenience for user interface design and color management. For example, in the application scenario of high-definition television, the chromaticity coordinate mapping diagram can directly guide engineers on how to adjust the driving parameters of each Micro-LED device to ensure that every pixel on the screen can present the color closest to the original image. The final chromaticity coordinate data not only reflects the ideal luminous characteristics of each Micro-LED device, but also provides a solid foundation for achieving high-quality and high-resolution image display. In summary, the above steps constitute a complete conversion process from spectral radiant power distribution to chromaticity coordinate data. It not only integrates a variety of advanced optical and color theory and technology, but also fully considers the needs and challenges of actual application scenarios. Through such detailed analysis and precise calculation, not only can the image quality be improved, but it can also provide valuable data support for future research and development, and promote the development of display technology towards higher quality.

[0036] In a specific embodiment, the pulse width modulation of the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform includes: Performing quantization frequency division processing on the chromaticity coordinate data to obtain quantized frequency data, and performing multi-cycle decomposition on the target micro-display device based on the quantized frequency data to obtain cycle decomposition data; wherein the cycle decomposition data includes a pulse frequency parameter, a cycle length parameter and a decomposition coefficient; Performing timing modulation calculation on the target micro display device based on the period decomposition data to obtain a modulation timing sequence, and performing sub-period expansion on the modulation timing sequence to obtain a sub-period modulation diagram; Performing pulse stretching processing based on the sub-period modulation diagram to obtain a stretch modulation spectrum, and performing light emission timing planning on a target micro-display device based on the stretch modulation spectrum to obtain timing planning data; Performing pulse phase alignment on the timing planning data to obtain a phase alignment sequence, and synthesizing a driving waveform on a target micro display device based on the phase alignment sequence to obtain waveform synthesis data; The waveform synthesis data is subjected to multiple modulation superposition to obtain a superimposed driving waveform, and the superimposed driving waveform is subjected to grayscale division through dynamic threshold screening to obtain a multi-level grayscale driving waveform.

[0037] Specifically, when implementing the above-mentioned steps, the process of pulse width modulation (PWM) of the target micro-display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform is a multi-level, multi-step technical implementation scheme. This process not only ensures that each Micro-LED micro-display device can accurately emit light according to the preset color and brightness requirements, but also provides key support for the performance optimization of the entire display system. First, the chromaticity coordinate data needs to be quantized and divided to obtain quantized frequency data. The quantized frequency division mentioned here refers to discretizing the continuous chromaticity coordinate values ​​and assigning them to different frequency intervals. For example, in the application scenario of a high-definition television playing a landscape documentary, when a blue sky or a green forest appears in the picture, the system will select a suitable frequency interval to divide the spectrum range according to the typical chromaticity coordinates corresponding to these colors. Through this quantized frequency division process, complex spectral information can be simplified into a series of discrete frequency points, which is convenient for subsequent processing. Then, based on these quantized frequency data, the target micro-display device is multi-cycle decomposed to obtain cycle decomposition data. Cycle decomposition is to subdivide a complete working cycle into multiple sub-cycles, each of which contains specific pulse frequency parameters, cycle length parameters and decomposition coefficients. For the blue sky in the landscape documentary, this means that the system can determine the most suitable pulse frequency and cycle length based on the color characteristics of the sky, so that each Micro-LED device can emit the correct light at the right time. With the cycle decomposition data, the next step is to perform timing modulation calculations on the target micro-display device to obtain a modulation timing sequence. The timing modulation calculation aims to determine the specific time schedule within each sub-cycle based on the cycle decomposition data, including when to turn on and off the light-emitting device. In this way, it can be ensured that each Micro-LED device can emit light accurately in the predetermined time sequence. Continuing with the landscape documentary as an example, when we want to show a rolling mountain range, the timing modulation calculation can help us accurately control the light-emitting moment of each pixel, making the outline of the mountain clearer and more three-dimensional. Subsequently, the modulation timing sequence is sub-cycle expanded to obtain a sub-cycle modulation diagram. Sub-cycle expansion is to expand the original compact timing sequence into a detailed sub-cycle diagram, which allows engineers to more intuitively see the specific working status of each sub-cycle, thereby further optimizing the luminous effect. Next, pulse stretching is performed based on the sub-cycle modulation diagram to obtain a stretching modulation spectrum. Pulse stretching refers to appropriately extending the duration of certain pulses to increase their duty cycle and thus enhance the luminous intensity. This operation is particularly useful for improving visibility in low-brightness areas. For example, when displaying a picture of the night sky, pulse stretching can make the stars appear brighter and more twinkling, increasing the visual impact. Then, the target micro-display device is light-emitting timing planned based on the stretch modulation spectrum to obtain the timing planning data.The purpose of light-emitting timing planning is to ensure that the timing between all related devices is coordinated and consistent, avoiding color deviation or image blur caused by time difference. Through the careful design of timing planning data, it can be ensured that each Micro-LED device can emit the most accurate light at the most appropriate time point, thereby presenting a high-quality image. In order to further optimize the driving waveform, it is also necessary to perform pulse phase alignment on the timing planning data to obtain a phase alignment sequence. Pulse phase alignment is to adjust the relative position between each pulse signal to ensure that they reach the peak or valley at the same time. This is very important for reducing electromagnetic interference and improving the stability of the system. Continuing with the example of landscape documentaries, when there are both fast-moving clouds and stationary mountains in the picture, phase alignment can ensure that the color transition between the two is natural and smooth, and no visual artifacts will be generated due to time mismatch. Finally, the target micro-display device is driven The waveform synthesis is synthesized based on the phase alignment sequence to obtain waveform synthesis data. The drive waveform synthesis prepares for the final generation of the actual drive signal. It comprehensively considers the results of all the previous steps to ensure that each device can receive the best driving waveform that matches it. After completing all the above steps, it is also necessary to perform multiple modulation superposition on the waveform synthesis data to obtain a superimposed driving waveform. Multiple modulation superposition is to combine modulation information of different levels to form a composite driving waveform. This method can not only improve the response speed of the system, but also enhance the detail expression of the image. For example, when displaying complex and changing city night scenes, multiple modulation superposition can make the lights of buildings more delicate and realistic, enhancing the realism of the overall picture. Finally, the superimposed driving waveform is divided into gray levels through dynamic threshold screening to obtain a multi-level grayscale driving waveform. Dynamic threshold screening is an intelligent algorithm that dynamically adjusts the grayscale division standard according to the actual display content to ensure that each grayscale level can be fully utilized. In this way, even under extreme conditions, such as high-contrast black and white photos or very dim environments, the display can maintain good visual effects and meet users' expectations for high-quality display effects. In summary, the above steps constitute a complete conversion process from chromaticity coordinate data to multi-level grayscale driving waveform. It not only integrates a variety of advanced signal processing technologies and algorithms, but also fully considers the needs and challenges of actual application scenarios. Through such detailed analysis and precise calculation, not only can the quality of the image be improved, but also valuable data support can be provided for future research and development, and display technology can be promoted to a higher quality direction.

[0038] In a specific embodiment, the sub-period expansion of the modulation timing sequence to obtain a sub-period modulation diagram includes: Extracting timing reference points from the modulation timing sequence to obtain a timing reference point set, and dividing the target micro-display device into sub-periods based on the timing reference point set to obtain a sub-period sequence; Calculating the duty cycle of the target micro-display device based on the sub-period sequence to obtain duty cycle data, and performing pulse density modulation on the duty cycle data to obtain a pulse density distribution diagram; Extending the pulse density distribution diagram on a time axis to obtain an extended pulse diagram, and performing waveform interpolation calculation based on the extended pulse diagram to obtain interpolation waveform data; Performing sub-period mapping on the interpolation waveform data to obtain a sub-period waveform diagram, and performing multi-level grayscale encoding on the target micro-display device based on the sub-period waveform diagram to obtain an encoded sub-period waveform diagram; The encoded sub-period waveform diagram is subjected to sub-period fusion through time sequence splicing to obtain a sub-period modulation diagram.

[0039] Specifically, when implementing the above-mentioned steps, the process of expanding the modulation timing sequence into sub-periods to obtain the sub-period modulation diagram is a precise and meticulous operation. This process aims to refine the originally compact timing information into multiple sub-periods, thereby providing more refined control instructions for each Micro-LED micro-display device to ensure that they can accurately emit light according to the preset color and brightness requirements. First, it is necessary to extract the timing reference points of the modulation timing sequence to obtain a set of timing reference points. The timing reference points here refer to time points with specific meanings in the entire light-emitting cycle, such as the time when key events such as turning on, off, or reaching maximum brightness occur. By identifying these reference points, the working state in each cycle can be more clearly understood, and the foundation for subsequent sub-period division can be laid. For example, in the application scenario of a high-definition television playing a landscape documentary, when a blue sky appears in the picture, the system will extract a series of timing reference points from the modulation timing sequence according to the color characteristics of the sky, such as the specific time when each pixel is lit and extinguished. Based on these sets of timing reference points, the target micro-display device can then be divided into sub-periods to obtain a sub-period sequence. Sub-period division is to subdivide a complete working cycle into several smaller time periods, each of which contains one or more timing reference points. For the blue sky picture, this means that the system can determine the most suitable sub-period length based on the frequency of sky color changes, so that each Micro-LED device can emit the correct light at the right time. After having a sub-period sequence, the next step is to calculate the duty cycle of the target micro-display device based on this to obtain the duty cycle data. The duty cycle refers to the proportion of time that the device is in the on state during a complete pulse cycle. It directly determines the average brightness level of the device and is therefore one of the important parameters affecting image quality. Continuing with the blue sky as an example, by calculating the duty cycle of each sub-period in the sub-period sequence, it is possible to determine the proportion of time that each Micro-LED device should remain lit to reproduce the closest to the real blue. Subsequently, the duty cycle data is pulse density modulated to obtain a pulse density distribution diagram. Pulse density modulation is a technology used to optimize pulse signals, which controls the average power output by adjusting the number of pulses per unit time. When dealing with complex natural scenes, such as the interlaced branches and leaves of trees in a forest, the pulse density distribution map can help engineers better balance the relationship between brightness and detail, so that the color of each leaf can be accurately reproduced. Next, the pulse density distribution map needs to be extended on the time axis to obtain an extended pulse map. The time axis extension is to expand the originally compact pulse sequence to make it easier for further analysis and processing. In this way, the time distribution of each pulse can be observed more intuitively, making it easier to discover potential problems and improve them. For example, when showing a picture of the night sky, the time axis extension will make the twinkling effect of the stars more obvious and increase the visual impact.Then, waveform interpolation calculation is performed based on the extended pulse graph to obtain interpolated waveform data. Waveform interpolation is to insert additional data points between two known data points to generate a smoother curve. This is very useful for reducing noise and artifacts in the image. By interpolating waveform data, the display effect can be made more delicate and realistic. In order to finally generate a sub-period modulation graph, it is also necessary to perform sub-period mapping on the interpolated waveform data to obtain a sub-period waveform graph. Sub-period mapping is to redistribute the interpolated waveform data to each sub-period to form a detailed sub-period waveform graph. This step not only retains the integrity of the original timing information, but also provides a solid foundation for subsequent multi-level grayscale encoding. For complex scenes in landscape documentaries, such as rolling mountains, sub-period waveform graphs can help ensure that the luminous behavior of each pixel is as expected, making the outline of the mountains clearer and more three-dimensional. Finally, multi-level grayscale encoding is performed on the target micro-display device based on the sub-period waveform graph to obtain the encoded sub-period waveform graph. Multi-level grayscale encoding is to discretize continuous brightness changes into multiple grayscale levels for practical application. In this way, not only can the response speed of the system be improved, but also the detail expression of the image can be enhanced. Finally, the encoded sub-period waveform graph is sub-period fused through time splicing to obtain a sub-period modulation graph. Time splicing is to seamlessly connect the waveform information of all sub-periods to form a complete modulation spectrum. This method ensures the temporal and spatial consistency throughout the entire luminous cycle, avoiding color deviation or image blur caused by time difference. For example, when showing fast-moving clouds and stationary mountains, sub-period fusion can ensure that the color transition between the two is natural and smooth, and no visual artifacts will be generated due to time mismatch. In summary, the above steps constitute a complete conversion process from modulation timing sequence to sub-period modulation graph. It not only integrates a variety of advanced signal processing technologies and algorithms, but also fully considers the needs and challenges of actual application scenarios. Through such meticulous analysis and precise calculation, not only can the quality of the image be improved, but also valuable data support can be provided for future research and development, and display technology can be promoted to a higher quality direction.

[0040] In a specific embodiment, the method of using a distributed control architecture to transmit a multi-level grayscale driving waveform to a corresponding target micro-display device to obtain a Micro-LED display image includes: Performing time division multiplexing encoding on the multi-level grayscale driving waveform to obtain waveform encoding data, and performing timing synchronization calculation on the target micro display device based on the waveform encoding data to obtain a synchronization timing matrix; Based on the synchronous timing matrix, driving signals of the target micro display device are grouped to obtain grouped driving data, and parallel tasks are assigned to the grouped driving data to obtain a task assignment sequence; Performing node topology construction on the task allocation sequence to obtain a control node topology map, and distributing data streams to the target micro-display device based on the control node topology map to obtain a distribution routing table; Performing concurrent control scheduling on the target micro-display device based on the distribution routing table to obtain a concurrent scheduling scheme, and performing clock synchronization coordination on the concurrent scheduling scheme to obtain a synchronous control instruction sequence; Distributing a driving signal to a target micro display device based on the synchronous control instruction sequence to obtain distribution control data; The distributed control architecture is used to transmit the distribution control data to the corresponding target micro-display device to obtain a Micro-LED display image.

[0041] Specifically, when implementing the above-mentioned steps, the process of transmitting the multi-level grayscale driving waveform to the corresponding target micro-display device using a distributed control architecture to obtain a Micro-LED display image is a complex and efficient operation. This process not only ensures that each Micro-LED micro-display device can receive a driving signal that matches it, but also provides a solid foundation for the performance optimization of the entire display system. First, it is necessary to perform time-division multiplexing encoding on the multi-level grayscale driving waveform to obtain waveform encoding data. Time division multiplexing (TDM) is a communication technology that allows multiple signals to share the same transmission channel and distinguish each signal by assigning different time slices. In the application scenario of high-definition television playing landscape documentaries, when the system needs to show a vast blue sky or a complex forest scene, by performing time-division multiplexing encoding on the multi-level grayscale driving waveform, these waveform information can be effectively compressed and organized so that they can be efficiently transmitted within a limited bandwidth. Next, the target micro-display device is subjected to timing synchronization calculation based on these waveform encoding data to obtain a synchronization timing matrix. The timing synchronization calculation is to ensure that all related devices perform the same operation at the same time point to avoid color deviation or image blur caused by time difference. For example, when showing fast-moving clouds and stationary mountains, the synchronous timing matrix can ensure that the color transition between the two is natural and smooth, and no visual artifacts will be generated due to time mismatch. With the synchronous timing matrix, the next step is to group the drive signals of the target micro-display device based on it to obtain grouped drive data. Drive signal grouping is to divide the device into several groups according to its location, function or other characteristics for easy management and scheduling. For complex scenes in landscape documentaries, such as rolling mountains, drive signal grouping can help engineers more finely control the luminous behavior in each area, making the outline of the mountains clearer and more three-dimensional. Subsequently, parallel task allocation is performed on the grouped drive data to obtain a task allocation sequence. Parallel task allocation refers to sending instructions to multiple processing units at the same time to improve processing speed and efficiency. In this way, not only can the transmission speed of the drive waveform be accelerated, but it can also better adapt to the working status of different devices, ensuring that each Micro-LED device can receive the correct drive signal in time. In order to further optimize the data transmission path, it is also necessary to construct the node topology of the task allocation sequence to obtain a control node topology diagram. Node topology construction is to determine the connection relationship between each node in the network to form an effective communication structure. This step is especially important for large display panels because it directly affects the speed and reliability of signal transmission. For example, when a high-definition TV plays a landscape documentary, the control node topology map can guide the system on how to most effectively transmit the drive signal from the central controller to each Micro-LED device, thereby reducing transmission delays and possible errors. Then, the data stream is distributed to the target micro-display device based on the control node topology map to obtain a distribution routing table.The distribution routing table records in detail the specific path of each data stream, including the starting point, the end point, and the nodes passed in the middle. Through such routing planning, it can be ensured that all driving signals can reach the destination accurately and accurately, improving the stability and consistency of the entire system. Next, based on the distribution routing table, the target micro-display device is concurrently controlled and scheduled to obtain a concurrent scheduling scheme. Concurrent control scheduling refers to coordinating the simultaneous execution of multiple tasks to make full use of system resources and improve overall performance. When processing complex image content, such as the twinkling effect of stars in the night sky, through concurrent control scheduling, the brightness change of each star can be accurately caused in a predetermined time sequence, which enhances the visual impact. Subsequently, the concurrent scheduling scheme is clock-synchronized and coordinated to obtain a synchronous control instruction sequence. Clock synchronization coordination is to ensure that all related devices work on the same time base, which is crucial to maintaining the consistency and stability of the image. Continuing to take the starry sky as an example, the synchronous control instruction sequence can ensure that the lighting and extinguishing moments of each star are completely consistent, without any time deviation. Finally, the target micro-display device is driven The signal is distributed based on the synchronous control instruction sequence to obtain distribution control data. The driving signal distribution is to send the final generated control instructions to the corresponding Micro-LED devices so that they can accurately emit light according to the preset parameters. This step directly determines the quality and perception of the image, so it must be accurate. For example, when showing a blue sky, the driving signal distribution can ensure that the blue tone of each pixel is as expected, presenting the closest visual effect to reality. Finally, the distributed control architecture is used to transmit the distributed control data to the corresponding target micro-display device to obtain the Micro-LED display image. The distributed control architecture allows multiple controllers or nodes to work together in the network, and each node is responsible for processing and transmitting the driving waveform information of the Micro-LED devices in a specific area. Compared with the centralized control system, the distributed control has higher flexibility and scalability. It can better adapt to the complex display panel layout and reduce signal transmission delay, thereby ensuring the consistency and real-time performance of the image display. In summary, the above steps constitute a complete conversion process from multi-level grayscale driving waveform to Micro-LED display image. It not only integrates a variety of advanced signal processing technologies and algorithms, but also fully considers the needs and challenges of actual application scenarios. Through such detailed analysis and precise calculation, not only can the image quality be improved, but it can also provide valuable data support for future research and development, and promote the development of display technology towards higher quality.

[0042] The above describes the driving control method of the Micro-LED micro display device in the embodiment of the present invention. The following describes the driving control device of the Micro-LED micro display device in the embodiment of the present invention. Figure 2In one embodiment of the present invention, a drive control device for a Micro-LED micro display device includes: A division module 21 is used to divide the target pixel area by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices; An analysis module 22 is used to perform electroluminescence spectrum analysis on a target micro display device based on the sub-pixel block to obtain a spectral radiation power distribution; wherein the Micro-LED micro display device is used as the target micro display device; A calculation module 23, configured to perform chromaticity calculation on a target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; A modulation module 24, configured to perform pulse width modulation on a target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; The transmission module 25 is used to transmit the multi-level grayscale driving waveform to the corresponding target micro display device by using a distributed control architecture to obtain a Micro-LED display image.

[0043] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to the above method embodiment, which will not be repeated here.

[0044] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0045] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0046] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0047] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0048] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0049] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for driving and controlling a Micro-LED micro display device, characterized in that: The following steps are involved: The target pixel area is divided by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices; Based on the sub-pixel block, an electroluminescence spectrum analysis is performed on the target micro-display device to obtain a spectral radiation power distribution; wherein the Micro-LED micro-display device is used as the target micro-display device; Performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; Performing pulse width modulation on the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; The distributed control architecture is used to transmit the multi-level grayscale driving waveform to the corresponding target micro-display device to obtain the Micro-LED display image.

2. The Micro-LED micro display device driving control method according to claim 1, characterized in that: The step of dividing the target pixel area by a preset display image to obtain sub-pixel blocks includes: Performing brightness feature analysis on a preset display image to obtain a pixel brightness distribution image, and performing boundary extraction on the pixel brightness distribution image to obtain an edge feature map; Performing adaptive threshold segmentation on the edge feature map to obtain a segmented boundary map; Performing a region growing operation on the target pixel region based on the segmented boundary map to obtain an initial sub-pixel region; A spatial clustering analysis is performed on the initial sub-pixel region to obtain a clustered sub-pixel block, and a center of gravity is located on the clustered sub-pixel block to obtain a located sub-pixel block.

3. The Micro-LED micro display device driving control method according to claim 1, characterized in that: The step of performing electroluminescence spectrum analysis on the target micro display device based on the sub-pixel block to obtain spectrum radiation power distribution includes: Calculating the spectral energy density of the target micro display device based on the sub-pixel block to obtain spectral energy density data; Performing spectral power density analysis based on the spectral energy density data to obtain a power density curve, and performing radiation power efficiency calculation on a target micro-display device based on the power density curve to obtain a radiation power efficiency graph; Calculating the radiation flux density of the radiation power efficiency diagram by a spectral integration operation method to obtain a radiation flux density distribution diagram; The spectral radiation characteristic of the target micro display device is analyzed based on the radiation flux density distribution diagram to obtain the spectral radiation power distribution.

4. The Micro-LED micro display device driving control method according to claim 1, characterized in that: The step of performing chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data includes: Dividing the spectral radiation power distribution into wavelength intervals to obtain wavelength segmentation data, and performing a spectral flux integration operation on the target micro-display device based on the wavelength segmentation data to obtain an integrated spectral flux diagram; Performing chromaticity mapping on the integrated spectral flux diagram by tristimulus value conversion technology to obtain a chromaticity mapping matrix, and normalizing the chromaticity coefficients of the chromaticity mapping matrix to obtain normalized chromaticity coefficients; Performing chromaticity space transformation on the target micro-display device based on the normalized chromaticity coefficient to obtain chromaticity space data; Performing color gamut boundary calculation on the chromaticity space data to obtain a color gamut boundary curve, and performing color purity analysis on the target micro-display device based on the color gamut boundary curve to obtain a color purity distribution diagram; wherein the color purity distribution diagram includes a color gamut range, boundary point coordinates, and color purity values; The color purity distribution diagram is coordinate mapped by a preset chromaticity coordinate conversion technology to obtain a chromaticity coordinate mapping diagram, and chromaticity coordinate data is determined based on the chromaticity coordinate mapping diagram.

5. The Micro-LED micro display device driving control method according to claim 1, characterized in that: The pulse width modulation of the target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform includes: Performing quantization frequency division processing on the chromaticity coordinate data to obtain quantized frequency data, and performing multi-cycle decomposition on the target micro-display device based on the quantized frequency data to obtain cycle decomposition data; wherein the cycle decomposition data includes a pulse frequency parameter, a cycle length parameter and a decomposition coefficient; Performing timing modulation calculation on the target micro display device based on the period decomposition data to obtain a modulation timing sequence, and performing sub-period expansion on the modulation timing sequence to obtain a sub-period modulation diagram; Performing pulse stretching processing based on the sub-period modulation diagram to obtain a stretch modulation spectrum, and performing light emission timing planning on a target micro-display device based on the stretch modulation spectrum to obtain timing planning data; Performing pulse phase alignment on the timing planning data to obtain a phase alignment sequence, and synthesizing a driving waveform on a target micro display device based on the phase alignment sequence to obtain waveform synthesis data; The waveform synthesis data is subjected to multiple modulation superposition to obtain a superimposed driving waveform, and the superimposed driving waveform is subjected to grayscale division through dynamic threshold screening to obtain a multi-level grayscale driving waveform.

6. The Micro-LED micro display device driving control method according to claim 5, characterized in that: The step of performing sub-period expansion on the modulation timing sequence to obtain a sub-period modulation diagram includes: Extracting timing reference points from the modulation timing sequence to obtain a timing reference point set, and dividing the target micro-display device into sub-periods based on the timing reference point set to obtain a sub-period sequence; Calculating the duty cycle of the target micro-display device based on the sub-period sequence to obtain duty cycle data, and performing pulse density modulation on the duty cycle data to obtain a pulse density distribution diagram; Extending the pulse density distribution diagram on a time axis to obtain an extended pulse diagram, and performing waveform interpolation calculation based on the extended pulse diagram to obtain interpolation waveform data; Performing sub-period mapping on the interpolation waveform data to obtain a sub-period waveform diagram, and performing multi-level grayscale encoding on the target micro-display device based on the sub-period waveform diagram to obtain an encoded sub-period waveform diagram; The encoded sub-period waveform diagram is subjected to sub-period fusion through time sequence splicing to obtain a sub-period modulation diagram.

7. The Micro-LED micro display device driving control method according to claim 1, characterized in that: The method of using a distributed control architecture to transmit a multi-level grayscale driving waveform to a corresponding target micro-display device to obtain a Micro-LED display image includes: Performing time division multiplexing encoding on the multi-level grayscale driving waveform to obtain waveform encoding data, and performing timing synchronization calculation on the target micro display device based on the waveform encoding data to obtain a synchronization timing matrix; Based on the synchronous timing matrix, driving signals of the target micro display device are grouped to obtain grouped driving data, and parallel tasks are assigned to the grouped driving data to obtain a task assignment sequence; Performing node topology construction on the task allocation sequence to obtain a control node topology map, and distributing data streams to the target micro-display device based on the control node topology map to obtain a distribution routing table; Performing concurrent control scheduling on the target micro-display device based on the distribution routing table to obtain a concurrent scheduling scheme, and performing clock synchronization coordination on the concurrent scheduling scheme to obtain a synchronous control instruction sequence; Distributing a driving signal to a target micro display device based on the synchronous control instruction sequence to obtain distribution control data; The distributed control architecture is used to transmit the distribution control data to the corresponding target micro-display device to obtain a Micro-LED display image.

8. A Micro-LED micro display device driving control device, characterized in that: include: A division module, used for dividing a target pixel area by a preset display image to obtain sub-pixel blocks; wherein the target pixel area is provided with a plurality of target micro-display devices; An analysis module, used for performing electroluminescence spectrum analysis on a target micro display device based on the sub-pixel block to obtain a spectrum radiation power distribution; wherein the Micro-LED micro display device is used as the target micro display device; A calculation module, used to perform chromaticity calculation on the target micro-display device based on the spectral radiation power distribution to obtain chromaticity coordinate data; A modulation module, used for performing pulse width modulation on a target micro display device based on the chromaticity coordinate data to obtain a multi-level grayscale driving waveform; The transmission module is used to transmit the multi-level grayscale driving waveform to the corresponding target micro-display device using a distributed control architecture to obtain a Micro-LED display image.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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