Pixel automatic calibration method of Micro LED display screen

Abstract

The invention discloses an automatic pixel calibration method for a Micro LED display screen, and the method comprises the steps: carrying out the multi-dimensional detection of the real-time brightness, color and temperature of each pixel through a high-precision multispectral sensor, obtaining the actual optical characteristics of each pixel, including but not limited to the parameters of brightness, color temperature, color difference, spectral response and the like, and carrying out the detection of the pixels; and deviation analysis: analyzing the detection data of each pixel through a deep learning algorithm, identifying brightness, color and current deviation, determining the correction demand of each pixel, and performing quantitative analysis on the deviation of each pixel. A high-precision multispectral sensor and a deep learning algorithm are introduced, so that the detection and calibration process of each pixel is more accurate. By dynamically adjusting the current output, the problems of pixel aging, uneven brightness, chromatic aberration and the like can be solved, so that the stability and consistency of the display effect are remarkably improved, and the service life of the Micro LED display screen is prolonged.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and specifically to a pixel automatic calibration method for a Micro LED display screen. Background Art

[0002] The pixel automatic calibration method for a Micro LED display screen is a method that, through intelligent algorithms and automated detection technologies, monitors and adjusts the brightness, color, and current output of each pixel on the display screen in real time to ensure the consistency and accuracy of the display effect. This method generally includes detecting the brightness and color of each pixel through high-precision sensors, and automatically adjusting the driving current of the corresponding pixel according to the detection results to correct problems such as uneven brightness, color difference, or dead pixels that may occur during manufacturing or use. Through this automatic calibration process, the visual effect of the display screen can be significantly improved, the uniformity and stability of the displayed content can be ensured, the service life of the display screen can be extended, and the time cost of manual intervention and manual calibration can be reduced.

[0003] In the prior art, although the pixel automatic calibration method for a Micro LED display screen can improve the display effect, there are still some drawbacks, mainly including: limited calibration accuracy: Most of the existing automatic calibration methods rely on hardware sensors and preset algorithms for pixel calibration, and the accuracy may be affected by factors such as sensor errors and algorithm limitations, resulting in inaccurate calibration results for the brightness or color of some pixels, especially in the case of high-resolution or small pixels; long calibration time: The existing pixel automatic calibration methods may take a long time to complete the calibration process of the entire display screen. Especially in the case of large-scale display screens or high resolutions, the long calibration time may affect production efficiency; highly affected by environmental factors: The existing methods often do not consider the influence of environmental factors such as temperature and humidity on the performance of the Micro LED display screen, and these factors may cause changes in the performance of the pixels, affecting the stability and consistency of the calibration results; high hardware cost: Automatic calibration requires relying on high-precision sensors and complex calibration circuits, which will increase production costs. Especially in large-scale production, the high cost of sensors may become a factor restricting its popularization; unable to calibrate in real time: Many existing automatic calibration methods are completed during the manufacturing process and cannot be calibrated in real time afterwards. This means that if pixels age or deviate during the use of the display screen, they cannot be corrected in time, resulting in a gradual degradation of the display effect; difficult to handle complex defect types: The existing technologies mainly focus on dealing with basic problems such as uneven brightness and color difference, while for more complex display defects such as dead pixels, flickering, and bright spots, the processing capabilities of the existing automatic calibration methods are limited and may not be able to completely solve these problems.

[0004] Therefore, we propose a pixel automatic calibration method for a Micro LED display screen. Summary of the Invention

[0005] To achieve the above object, the present invention provides the following technical solution: A pixel automatic calibration method for a Micro LED display screen, comprising the following steps:

[0006] S1: Pixel detection: Use a high-precision multi-spectral sensor to perform multi-dimensional detection of the real-time brightness, color, and temperature of each pixel, and obtain the actual optical characteristics of each pixel, including but not limited to parameters such as brightness, color temperature, color difference, and spectral response;

[0007] S2: Deviation analysis: Analyze the detection data of each pixel through a deep learning algorithm, identify brightness, color, and current deviations, determine the correction requirements for each pixel, and perform quantitative analysis on the deviations of each pixel;

[0008] S3: Dynamic calibration: According to the results of the deviation analysis, adopt an adaptive current adjustment technology to automatically adjust the driving current of each pixel to correct brightness non-uniformity, color deviation, aging effect, and other potential display defects;

[0009] S4: Environmental adaptability calibration: Real-time detect the environmental changes of the display screen through a built-in environmental monitoring system (such as temperature and humidity sensors), and perform dynamic compensation on the driving current of each pixel according to the environmental changes to ensure the stability of the display effect under different environmental conditions;

[0010] S5: Real-time feedback adjustment: Establish a real-time adjustment mechanism based on a feedback loop, continuously monitor the state of each pixel during the operation of the display screen, and automatically adjust the driving current according to the changes to ensure the long-term stability of the display effect;

[0011] S6: Self-diagnosis and repair: Automatically identify pixel defects (such as dead pixels, bright pixels, color differences, etc.) through an intelligent diagnosis system, and perform local repair and adjustment on the defective areas to optimize the display effect and extend the service life of the display screen.

[0012] Preferably, the deep learning algorithm is based on a convolutional neural network (CNN) model, which can be trained through historical data to achieve efficient identification and correction of pixel deviations, and this model can be dynamically optimized according to the size, resolution, and usage environment of the display screen.

[0013] Preferably, the high-precision multi-spectral sensor can simultaneously detect the optical characteristics in the range from visible light to infrared spectrum to comprehensively evaluate the pixel performance, and its spectral resolution is not less than 1nm, which can accurately capture the optical characteristics of each pixel.

[0014] Preferably, the adaptive current regulation technology includes using a high-precision current source module to adjust the current output of each pixel in real time according to pixel detection data, with an adjustment accuracy reaching the microamp level, so as to achieve uniform brightness and color.

[0015] Preferably, the environmental adaptability calibration monitors the working environment of the display screen in real time through environmental sensors, including temperature, humidity, light intensity, etc., and adjusts the pixel driving current according to environmental changes to improve display stability and ensure that the display screen always maintains a high-quality display effect under environmental changes.

[0016] Preferably, the self-diagnosis and repair system is based on image processing technology, which can monitor and identify defective areas (such as dead pixels, bright pixels, uneven brightness, etc.) in the display screen in real time, and automatically perform local repair and adjustment to optimize the display effect.

[0017] Compared with the prior art, the present invention provides a pixel automatic calibration method for a Micro LED display screen, which has the following beneficial effects:

[0018] 1. For the pixel automatic calibration method of this Micro LED display screen, by introducing a high-precision multi-spectral sensor and a deep learning algorithm, the detection and calibration process of each pixel becomes more accurate. By dynamically adjusting the current output, problems such as pixel aging, uneven brightness, and color difference can be solved, thereby significantly improving the stability and consistency of the display effect and extending the service life of the Micro LED display screen.

[0019] 2. For the pixel automatic calibration method of this Micro LED display screen, based on deep learning and adaptive regulation technology, it can automatically adjust the pixel driving current of the display screen according to different environments and usage conditions (such as temperature, humidity, light intensity, etc.) to achieve real-time pixel calibration without manual intervention. This intelligent and adaptive calibration method improves production efficiency and reduces labor costs.

[0020] 3. For the pixel automatic calibration method of this Micro LED display screen, the impact of environmental changes on the display effect is an important issue in display technology. By integrating environmental sensors, the method can detect and adjust the driving current in real time, making the display effect always stable under different environmental conditions. Especially in extreme environments such as high temperature, low temperature, or high humidity, the display screen can still maintain high-quality display.

[0021] 4. For the pixel automatic calibration method of this Micro LED display screen, by introducing an automatic diagnosis and repair function, it can detect and repair defects such as dead pixels, bright pixels, and color difference in the display screen, avoiding the decline in display quality caused by these defects during the use of the display screen. The local repair function effectively improves the overall performance and user experience of the display screen.

[0022] 5. The pixel automatic calibration method of the Micro LED display screen can perform large-scale and rapid automatic calibration on the production line by using high-precision sensors and deep learning models, with high production efficiency, meeting the needs of large-scale production while maintaining low production costs.

[0023] 6. The pixel automatic calibration method of the Micro LED display screen can accurately adjust each pixel by adopting microamp-level current regulation technology, eliminating display problems caused by current fluctuations. This can ensure the consistency of brightness and color of each pixel, thereby achieving high-quality display effects. Detailed implementation manners

[0024] The technical solutions in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] Embodiment

[0026] An embodiment of a pixel automatic calibration method for a Micro LED display screen

[0027] A pixel automatic calibration method for a Micro LED display screen includes the following steps:

[0028] S1: Pixel detection: Use a high-precision multi-spectral sensor to perform multi-dimensional detection of the real-time brightness, color, and temperature of each pixel, and obtain the actual optical characteristics of each pixel, including but not limited to parameters such as brightness, color temperature, color difference, and spectral response;

[0029] S2: Deviation analysis: Analyze the detection data of each pixel through a deep learning algorithm, identify brightness, color, and current deviations, determine the correction requirements for each pixel, and perform quantitative analysis on the deviations of each pixel;

[0030] S3: Dynamic calibration: According to the results of the deviation analysis, adopt an adaptive current regulation technology to automatically adjust the driving current of each pixel to correct brightness non-uniformity, color deviation, aging effect, and other potential display defects;

[0031] S4: Environmental adaptability calibration: Real-time detect the environmental changes of the display screen through a built-in environmental monitoring system (such as temperature and humidity sensors), and perform dynamic compensation on the driving current of each pixel according to the environmental changes to ensure the stability of the display effect under different environmental conditions;

[0032] S5: Real-time feedback adjustment: Establish a real-time adjustment mechanism based on a feedback loop. During the operation of the display screen, continuously monitor the status of each pixel, and automatically adjust the driving current according to the changes to ensure the long-term stability of the display effect;

[0033] S6: Self-diagnosis and repair: Through an intelligent diagnosis system, automatically identify pixel defects (such as dead pixels, bright pixels, color differences, etc.), and perform local repair and adjustment on the defective areas to optimize the display effect and extend the service life of the display screen.

[0034] Specifically, the deep learning algorithm is based on a convolutional neural network (CNN) model, which can be trained through historical data to achieve efficient identification and correction of pixel deviations, and this model can be dynamically optimized according to the size, resolution, and usage environment of the display screen.

[0035] Specifically, the high-precision multi-spectral sensor can simultaneously detect the optical characteristics in the range from visible light to infrared spectrum to comprehensively evaluate the pixel performance, and its spectral resolution is not less than 1nm, which can accurately capture the optical characteristics of each pixel.

[0036] Specifically, the adaptive current adjustment technology includes using a high-precision current source module to adjust the current output of each pixel in real time according to the pixel detection data, and the adjustment accuracy reaches the microamp level to achieve uniform brightness and color.

[0037] Specifically, the environmental adaptability calibration uses environmental sensors to continuously monitor the working environment of the display screen, including temperature, humidity, light intensity, etc., and adjusts the pixel driving current according to the environmental changes to improve the display stability and ensure that the display screen always maintains a high-quality display effect under environmental changes.

[0038] Specifically, the self-diagnosis and repair system is based on image processing technology, which can continuously monitor and identify the defective areas (such as dead pixels, bright pixels, uneven brightness, etc.) in the display screen, and automatically perform local repair and adjustment to optimize the display effect.

[0039] Through the above technical solutions, in the present invention, by introducing a high-precision multi-spectral sensor and a deep learning algorithm, the detection and calibration process of each pixel is made more precise. By dynamically adjusting the current output, problems such as pixel aging, brightness non-uniformity, and color difference can be solved, thereby significantly improving the stability and consistency of the display effect and extending the service life of the Micro LED display screen; based on deep learning and adaptive adjustment technologies, the pixel drive current of the display screen can be automatically adjusted according to different environments and usage conditions (such as temperature, humidity, light intensity, etc.), realizing real-time pixel calibration without manual intervention. This intelligent and adaptive calibration method improves production efficiency and reduces labor costs; the impact of environmental changes on the display effect is an important issue in display technology. By integrating environmental sensors, the method can detect and adjust the drive current in real time, ensuring that the display effect remains stable under different environmental conditions. Especially in extreme environments such as high temperature, low temperature, or high humidity, the display screen can still maintain high-quality display; by introducing an automatic diagnosis and repair function, defects such as dead pixels, bright pixels, and color difference in the display screen can be detected and repaired, avoiding the degradation of the display quality caused by these defects during the use of the display screen. The local repair function effectively improves the overall performance and user experience of the display screen; by using high-precision sensors and deep learning models, large-scale and rapid automated calibration can be carried out on the production line, with high production efficiency, meeting the requirements of large-scale production while maintaining low production costs; by adopting microamp-level current adjustment technology, precise adjustment of each pixel can be achieved, eliminating display problems caused by current fluctuations. This can ensure the consistency of brightness and color of each pixel, thus achieving a high-quality display effect.

[0040] Pixel detection process: During the production process of the display screen, a multi-spectral sensor is first used on the production line to detect each pixel of the display screen. The sensor can detect the optical characteristics from visible light to near-infrared spectrum, and multi-dimensional data such as the brightness, color temperature, and color difference of each pixel will be recorded in real time. To improve the measurement accuracy, the spectral resolution of the sensor is not less than 1nm, ensuring accurate evaluation of each pixel.

[0041] Deep learning algorithm: Through the collected data, a convolutional neural network (CNN) model is used to analyze the brightness, color, and current deviation of each pixel. The algorithm can efficiently identify the deviation and train a model based on historical data that can accurately predict and correct the deviation. The model will also be dynamically optimized according to the size, resolution, and usage environment of the display screen to adapt to different products and environments.

[0042] Adaptive Current Regulation: Based on the deviation analyzed by the deep learning algorithm, the system will automatically adjust the driving current of each pixel. The current output of each pixel can be precisely adjusted at the microamp level to ensure the uniformity of the display effect. The adjustment process uses a high-precision current source module to guarantee the accuracy and stability of current regulation.

[0043] Environmental Adaptability Calibration: After the display screen is installed, a real-time environmental monitoring system (such as temperature and humidity sensors) will monitor the changes in temperature and humidity of the working environment. According to the environmental data, the system will automatically adjust the driving current to adapt to environmental changes. For example, when the environmental temperature rises, the system will automatically reduce the current output to prevent the attenuation of the display effect caused by excessive temperature.

[0044] Real-time Feedback and Self-repair: After the display screen is put into use, the system will continuously monitor the display effect and automatically adjust the driving current of the pixels through a feedback loop. If uneven pixel brightness or problems such as dead pixels and bright pixels are detected, the system will perform self-diagnosis based on image processing technology and locally repair the defective areas to ensure the stability of the display effect.

[0045] Production and Testing Phase: During the production process, the entire pixel calibration process is automatically completed without manual intervention in the factory. Through automated detection and repair, the production efficiency is greatly improved, and at the same time, the rework cost caused by human error is reduced. The final product can quickly enter the market and ensure excellent display effects.

[0046] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for automatic pixel calibration of a Micro LED display, characterized in that: The following steps are involved: S1: Pixel detection: Use a high-precision multispectral sensor to perform real-time multi-dimensional detection of brightness, color and temperature of each pixel to obtain the actual optical characteristics of each pixel, including but not limited to brightness, color temperature, color difference, spectral response and other parameters; S2: Deviation analysis: Analyze the detection data of each pixel through deep learning algorithms, identify brightness, color and current deviations, determine the correction requirements of each pixel, and perform quantitative analysis of the deviation of each pixel; S3: Dynamic Calibration: Based on the results of the deviation analysis, adaptive current regulation technology is used to automatically adjust the drive current of each pixel to correct uneven brightness, color deviation, aging effects and other potential display defects; S4: Environmental adaptability calibration: The built-in environmental monitoring system (such as temperature and humidity sensors) is used to detect the environmental changes of the display screen in real time, and the driving current of each pixel is dynamically compensated according to the environmental changes to ensure the stability of the display effect under different environmental conditions; S5: Real-time feedback regulation: Establish a real-time regulation mechanism based on a feedback loop to continuously monitor the status of each pixel during the operation of the display screen, and automatically adjust the driving current according to the changes to ensure the long-term stability of the display effect; S6: Self-diagnosis and repair: Through the intelligent diagnosis system, it can automatically identify pixel defects (such as dead pixels, bright spots, color differences, etc.), and perform local repairs and adjustments on the defective areas to optimize the display effect and extend the service life of the display.

2. The method for automatically calibrating pixels of a Micro LED display according to claim 1, characterized in that: The deep learning algorithm is based on a convolutional neural network (CNN) model, which can be trained with historical data to achieve efficient identification and correction of pixel deviations, and the model can be dynamically optimized according to the size, resolution and usage environment of the display screen.

3. The method for automatically calibrating pixels of a Micro LED display according to claim 1, wherein: The high-precision multi-spectral sensor can simultaneously detect optical properties from visible light to infrared spectrum to comprehensively evaluate pixel performance, and its spectral resolution is not less than 1nm, which can accurately capture the optical properties of each pixel.

4. The method for automatically calibrating pixels of a Micro LED display according to claim 1, wherein: The adaptive current regulation technology includes using a high-precision current source module to adjust the current output of each pixel in real time according to the pixel detection data, with the regulation accuracy reaching the microampere level to achieve uniform brightness and color.

5. The method for automatically calibrating pixels of a Micro LED display according to claim 1, wherein: The environmental adaptability calibration described above monitors the working environment of the display screen in real time through environmental sensors, including temperature, humidity, light intensity, etc., and adjusts the pixel driving current according to environmental changes to improve display stability and ensure that the display screen always maintains high-quality display effects under environmental changes.

6. The method for automatically calibrating pixels of a Micro LED display according to claim 1, wherein: The self-diagnosis and repair system is based on image processing technology, which can monitor and identify defective areas in the display screen (such as dead spots, bright spots, uneven brightness, etc.) in real time, and automatically perform local repair and adjustment to optimize the display effect.