A high-precision pixel automatic correction method for a glass-based display screen

Abstract

The present invention discloses a high-precision pixel automatic correction method for a glass-based display screen, which includes the following steps: data acquisition, pixel position and brightness mapping modeling, error detection and correction data calculation, pixel correction and control circuit implementation, and dynamic adaptive adjustment mechanism. The present invention has the following advantages and effects: The present invention can monitor and correct each pixel of the display screen in real time to ensure high-precision display effects under different environmental conditions; at the same time, the pixel correction realizes fully automated and high-precision control from data acquisition, modeling to error detection, correction and dynamic adjustment, which not only significantly improves the display effect of the display screen, but also has good environmental adaptability and applicability, meeting the requirements for high-quality display effects in different scenarios.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and particularly to a high-precision pixel automatic correction method for a glass-based display screen. Background Art

[0002] With the continuous development of display technology, especially the wide application of display technologies such as OLED, LCD, LED, and micro-LED, display screens have become a core component in many high-end devices, and the accuracy and stability of the display effect have become an important guarantee for the user experience. However, during actual use, display screens are easily affected by various factors. Especially in scenarios with high-precision requirements, the display effect may deteriorate due to deviations in pixel position, brightness, and color.

[0003] Common display screen defects include:

[0004] Uneven brightness: Due to the production process or long-term use, the brightness of some areas may decay, resulting in lower or higher brightness in some areas of the display screen.

[0005] Color deviation: Different production batches, material differences, and working environments (such as temperature, humidity, etc.) will cause inconsistent color performance of the display screen.

[0006] Inaccurate pixel position: Due to minor deformations during the manufacturing process of the display screen, the accurate position of the pixel points may shift, resulting in an unsatisfactory display effect.

[0007] To overcome these problems, pixel correction technology has gradually become an important means to solve high-precision display problems. Especially in high-end display devices, the brightness and color of each pixel are accurately corrected to ensure the uniformity and accuracy of the display effect. Traditional pixel correction methods generally rely on static correction data, and in some dynamic environments, the correction of the display screen still cannot adapt to real-time changes in a timely manner. Therefore, the present invention proposes a high-precision pixel automatic correction method for a glass-based display screen, which can monitor and correct each pixel of the display screen in real time to ensure high precision of the display effect under different environmental conditions. Summary of the Invention

[0008] The purpose of the present invention is to provide a high-precision pixel automatic correction method for a glass-based display screen to solve the problems raised in the background art.

[0009] The above technical purpose of the present invention is achieved through the following technical solutions:

[0010] A high-precision pixel automatic correction method for a glass-based display screen includes the following steps:

[0011] Step S1, data collection: by installing a high-precision sensor device on the surface or inner layer of the display screen, the brightness, color and position information of each pixel on the display screen is collected in real time, and the data is transmitted to the data processing system;

[0012] Step S2, pixel position and brightness mapping modeling: the data processing system receives the data and accurately models the brightness, color and position information of each pixel in the display screen, providing accurate data support for subsequent data correction and optimization;

[0013] Step S3, error detection and correction data calculation; based on the pixel position and brightness mapping modeling, further data correction and optimization are performed;

[0014] Step S4, pixel correction and control circuit implementation; the calculated correction data of each pixel is transmitted to the control circuit of the display screen, and the control circuit adjusts the driving current of the display screen according to the correction data, thereby realizing automatic correction of the brightness, color and position accuracy of the pixel point, ensuring that the display effect meets the expected standard;

[0015] Step S5, dynamic adaptive adjustment mechanism: During the display process, the environmental conditions of the display screen are monitored in real time, and the correction data are dynamically adjusted.

[0016] By adopting the above technical solution, high-precision sensors are used to collect the brightness, color and position information of each pixel in real time, and automatic correction is performed to effectively reduce the impact of uneven brightness, color deviation and pixel position error; from data collection to error detection and correction, and then to dynamic adjustment, it is ensured that the display effect always meets the expected standards and reduces human intervention; by real-time monitoring of environmental conditions and dynamic adjustment of correction data, the consistency and stability of the display effect in different environments is guaranteed.

[0017] Further configuration is that the step S2 is specifically:

[0018] Step S21: After data collection is completed, the collected raw data must be preprocessed to provide more accurate input for subsequent pixel position and brightness mapping modeling;

[0019] Step S22: After the data preprocessing is completed, the modeling stage of pixel position and brightness mapping is entered, the purpose of which is to convert the collected brightness and position data of each pixel into a mathematical model that can accurately represent the state of the display screen;

[0020] Step S23: After constructing the pixel position and brightness mapping model, the display screen is calibrated using the model to optimize the brightness and position of each pixel to achieve a predetermined display effect.

[0021] By adopting the above technical solutions, the pre-processing of the collected data, such as smoothing and normalization, provides accurate input for brightness and position mapping modeling; the brightness, position and other data of each pixel are converted into a mathematical model that accurately reflects the state of the display screen, providing a reliable basis for subsequent correction and optimization.

[0022] Further configuration is that the step S21 is specifically as follows:

[0023] Step S211, smoothing the collected data by using a Gaussian filtering algorithm to remove the influence of noise existing in the data collection process on subsequent modeling, and retaining the main features of the data and removing random fluctuations by setting appropriate filtering parameters;

[0024] Step S212: Different high-precision sensor devices and display screens with different screen sizes and resolutions will result in different ranges of collected data; by normalizing the brightness and color information of each pixel, the value range of the data is within a unified standard range;

[0025] Step S212: perform outlier detection using a robust regression algorithm and remove abnormal data points to ensure the reliability of the final data set.

[0026] By adopting the above technical solution, the noise in the collected data is removed through the Gaussian filtering algorithm, the data characteristics are effectively retained, and the modeling accuracy is improved; the combination of normalization processing and robust regression algorithm can eliminate outliers, ensure the uniformity and reliability of input data, and adapt to display screens of different devices and resolutions.

[0027] A further configuration is to introduce a Kalman filter algorithm in step S22. The Kalman filter algorithm combines the current error with the past state data through recursive calculation, thereby dynamically adjusting the mapping model to minimize the error and ensure the accuracy and stability of the model.

[0028] By adopting the above technical solution, the Kalman filter algorithm is introduced to combine historical status and current data, and the model is dynamically adjusted to ensure the accuracy and stability of modeling.

[0029] Further configuration is that the step S3 is specifically:

[0030] Step S31, pixel error detection and identification:

[0031] Step S32, correcting the pixel points to be corrected at the identified location;

[0032] Step S33: Real-time correction and feedback adjustment of pixels.

[0033] Further configuration is that the step S31 is specifically as follows:

[0034] Suppose the brightness and color of the pixel after being corrected by the pixel position and brightness mapping model are respectively and , while the brightness and color under the ideal display standard are respectively and . The following error formula is adopted to calculate the deviation of brightness and color:

[0035] ,

[0036] ,

[0037] wherein, represents the brightness error; represents the color error;

[0038] During the error detection process, it is first necessary to calculate the brightness error and color error of each pixel by traversing all pixels, and then identify which pixels have errors exceeding the preset tolerance range as the target pixels to be corrected by statistically analyzing the distribution of errors.

[0039] By adopting the above technical solution, the deviation formula of brightness and color is used to quickly identify the pixels whose errors exceed the tolerance range, realizing the screening of accurate correction targets; based on the statistical analysis of error distribution, it provides a scientific basis for the correction process, improving the overall uniformity and visual effect of the display screen.

[0040] A further setting is that the specific step S32 is as follows:

[0041] Step S321: Calculate the correction parameters based on the least squares method and by minimizing the sum of the squares of the errors, so that the corrected brightness and color of each pixel are close to the ideal values;

[0042] Suppose there are multiple pixels N, and the error of each pixel consists of the brightness error and the color error . The objective function of the least squares method can be written as:

[0043] ,

[0044] By optimizing the above objective function, an optimal correction data set and can be obtained;

[0045] Step S322: On some display screens, the brightness and color errors of pixels may not be linearly distributed. In this case, a non-linear regression method is required to calculate the error correction value more precisely; suppose the relationship between the brightness error and the position can be represented by a non-linear function:

[0046] ,

[0047] Among them, , represent the horizontal and vertical coordinates of the pixel point; is a non-linear function, representing the relationship between pixel brightness and position; is the error term;

[0048] By fitting and optimizing the above non-linear model, the optimal calibration function is obtained, and it is used to calibrate the brightness and color of the pixel point.

[0049] By adopting the above technical solution, using the least squares method and the non-linear regression method, the sum of the squares of the errors of brightness and color is minimized to ensure that the pixel points after calibration are closer to the ideal display value; non-linear regression can better adapt to the non-linear distribution of errors and improve the accuracy and display effect of calibration.

[0050] A further setting is that the specific step S33 is as follows:

[0051] Step S331: After step S32, the calibration data set and are obtained. These calibration data will be applied to the control circuit of the display screen to correct the brightness and color deviation of the pixel points;

[0052] The brightness and color calibration of each pixel point can be adjusted in the following way:

[0053] ,

[0054] ,

[0055] Among them, is the calibrated brightness, is the calibrated color; these calibrated data will control the display effect of each pixel point through the control circuit of the display screen;

[0056] Step S332: The real-time error feedback is adjusted by monitoring the display effect of the screen in real time and the error value calculated by error detection; the feedback mechanism is usually based on the PID control algorithm, aiming to adjust the calibration data according to the size and trend of the error to ensure the continuity and consistency of the display effect;

[0057] Assume that the error of the current display effect is , and the update of the calibration parameter can be expressed as:

[0058] ,

[0059] ,

[0060] Among them, , , are the proportional, integral, and derivative coefficients of the PID controller, is the current error, and are the new calibration data; represents the integral term, where represents the integral of the error from the initial moment to the current moment;

[0061] Based on the above feedback adjustment, the calibration parameters can be continuously adjusted to keep the display screen in the best display effect during actual application.

[0062] By adopting the above technical solution, applying the calibration data set to the control circuit, dynamically adjusting the brightness and color of each pixel, correcting the deviation, and achieving the best display effect; introducing the real-time error feedback of the PID control algorithm, dynamically adjusting the calibration parameters, and ensuring the consistency and stability of the display screen during long-term operation

[0063] A further setting is that the specific step S4 is as follows:

[0064] Step S41, the brightness correction signal is achieved by adjusting the voltage or current of each pixel of the display screen; the brightness control signal is expressed as:

[0065] ,

[0066] Among them, is the brightness correction value of pixel i; is the maximum voltage that this pixel can reach; is the gamma value of brightness adjustment; represents a non-linear function;

[0067] The above formula indicates that by the brightness correction value adjust the voltage signal of this pixel to achieve the corrected brightness effect;

[0068] Step S42, assuming that the color of each pixel is determined by the current intensity of the RGB three channels, the color correction control signal is expressed as:

[0069] ,

[0070] Among them, is the color correction value of pixel i; is the maximum current that this pixel can reach; is the gamma value of color adjustment; represents a non - linear function;

[0071] The above formula indicates that by the color correction value εC i , the current changes of the three RGB channels are driven, thereby correcting the color of the pixel;

[0072] Step S43: Assume that the signal received by the driving circuit is a current signal and , and correspond to brightness and color respectively, then its drive control can be expressed as:

[0073] ,

[0074] ,

[0075] wherein, and are the gain coefficients of the driving circuit, corresponding to brightness and color adjustment respectively; and are the current signals finally input to each pixel of the display screen;

[0076] By adjusting these current signals, the brightness and color of each pixel of the display screen will be accurately corrected according to the correction value.

[0077] By adopting the above technical solution, the driving current of the display screen is adjusted through the current control signals of brightness and color, realizing the brightness and color correction of each pixel and improving the accuracy of the display effect; the adjustment of the current signal can be compatible with driving circuits with different gain coefficients, enhancing the applicability of the method.

[0078] A further setting is that the specific step S5 is as follows:

[0079] The temperature and humidity values in the environment are monitored through a temperature sensor and a humidity sensor, and by weighted synthesis of the influences of different environmental conditions, the correction amount of each pixel is calculated;

[0080] ,

[0081] wherein,

[0082] and are the correction coefficients of the influence of temperature and humidity on brightness; represents the current actual brightness; represents the adjusted brightness after environmental compensation;

[0083] and are the change amounts of temperature and humidity respectively.

[0084] By adopting the above technical solution, the environmental changes are monitored by the temperature and humidity sensors, and the brightness correction value is dynamically adjusted, so that the display screen can still maintain the expected display effect in a changing environment; the influence of temperature and humidity on brightness is quantified by using the correction formula, providing a more comprehensive correction mechanism.

[0085] In summary, the present invention can monitor and correct each pixel of the display screen in real time to ensure high-precision display effects under different environmental conditions; at the same time, the pixel correction realizes fully automated and high-precision control from data acquisition, modeling to error detection, correction and dynamic adjustment. It not only significantly improves the display effect of the display screen, but also has good environmental adaptability and applicability, meeting the requirements for high-quality display effects in different scenarios. Description of the Drawings

[0086] Figure 1 It is a schematic diagram of the overall process of the embodiment;

[0087] Figure 2 It is a test data table for Application Example 1;

[0088] Figure 3 It is a test data table for Application Example 2. Detailed Description of the Invention

[0089] The present invention will be further described in detail below with reference to the accompanying drawings.

[0090] As shown in the Figure 1 accompanying drawings;

[0091] This embodiment discloses a high-precision pixel automatic correction method for a glass-based display screen, including the following steps:

[0092] Step S1, data acquisition; through a high-precision sensor device installed on the surface or inner layer of the display screen, the brightness, color and position information of each pixel on the display screen are collected in real time, and these data are transmitted to the data processing system;

[0093] Specifically, the surface or inner layer of the display screen is divided into several small areas, and each small area is separately configured with a high-precision sensor device to be responsible for collecting the pixel information in the small area; in order to further improve the accuracy of data acquisition, this embodiment uses infrared sensing technology combined with photoelectric induction to enhance the sensing ability for extremely small brightness changes.

[0094] Step S2, pixel position and brightness mapping modeling; the data processing system receives the data and accurately models the brightness, color and position information of each pixel in the display screen, providing accurate data support for subsequent data correction and optimization;

[0095] Step S3, error detection and correction data calculation; based on the pixel position and brightness mapping modeling, further data correction and optimization are performed;

[0096] Step S4, pixel correction and control circuit implementation; the calculated correction data of each pixel is transmitted to the control circuit of the display screen, and the control circuit adjusts the driving current of the display screen according to the correction data, thereby realizing automatic correction of the brightness, color and position accuracy of the pixel point, ensuring that the display effect meets the expected standard;

[0097] Step S5, dynamic adaptive adjustment mechanism: During the display process, the environmental conditions of the display screen are monitored in real time, and the correction data are dynamically adjusted.

[0098] Among them, step S2 is specifically:

[0099] Step S21: After data collection is completed, the collected raw data must be preprocessed to provide more accurate input for subsequent pixel position and brightness mapping modeling;

[0100] Step S22: After the data preprocessing is completed, the modeling stage of pixel position and brightness mapping is entered, the purpose of which is to convert the collected brightness and position data of each pixel into a mathematical model that can accurately represent the state of the display screen;

[0101] Step S23: After constructing the pixel position and brightness mapping model, the display screen is calibrated using the model to optimize the brightness and position of each pixel to achieve a predetermined display effect.

[0102] Among them, step S21 is specifically as follows:

[0103] Step S211, smoothing the collected data by using a Gaussian filtering algorithm to remove the influence of noise existing in the data collection process on subsequent modeling, and retaining the main features of the data and removing random fluctuations by setting appropriate filtering parameters;

[0104] Step S212: Different high-precision sensor devices and display screens with different screen sizes and resolutions will result in different ranges of collected data; by normalizing the brightness and color information of each pixel, the value range of the data is within a unified standard range;

[0105] Step S212: perform outlier detection using a robust regression algorithm and remove abnormal data points to ensure the reliability of the final data set.

[0106] Among them, the Kalman filtering algorithm is introduced in step S22. Through recursive calculation, the Kalman filtering algorithm combines the current error with past state data, thereby dynamically adjusting the mapping model to minimize the error and ensure the accuracy and stability of the model.

[0107] Among them, step S3 is specifically as follows:

[0108] Step S31, error detection and recognition of pixel points:

[0109] Step S32, correct the pixel points to be corrected identified;

[0110] Step S33, real-time correction and feedback adjustment of pixel points.

[0111] Among them, step S31 is specifically as follows:

[0112] Assume that the brightness and color of the pixel points after being corrected by the pixel position and brightness mapping model are and , while the brightness and color under the ideal display standard are and , and the following error formulas are used to calculate the deviations of brightness and color:

[0113] ,

[0114] ,

[0115] Among them, represents the brightness error; represents the color error;

[0116] During the error detection process, first, it is necessary to calculate the brightness error and color error of each pixel point by traversing all pixel points, and then identify which pixel points have errors exceeding the preset tolerance range as the target pixels to be corrected by statistically analyzing the distribution of errors.

[0117] Among them, step S32 is specifically as follows:

[0118] Step S321, calculate the correction parameters based on the least squares method and by minimizing the sum of the squares of the errors, so that the corrected brightness and color of each pixel point are close to the ideal values;

[0119] Assume there are multiple pixel points N, and the error of each pixel point consists of the brightness error and the color error , and the objective function of the least squares method can be written as:

[0120] ,

[0121] By optimizing the above objective function, an optimal calibration data set can be obtained. and ;

[0122] Step S322: On some displays, the brightness and color errors of pixels may not be linearly distributed. In this case, a non-linear regression method is needed to calculate the error correction value more precisely. Assume that the relationship between the brightness error and the position can be represented by a non-linear function:

[0123] ,

[0124] where, , represents the horizontal and vertical coordinates of the pixel; is a non-linear function representing the relationship between pixel brightness and position; is the error term;

[0125] By fitting and optimizing the above non-linear model, the optimal calibration function is obtained and used to correct the brightness and color of the pixel.

[0126] Among them, step S33 is specifically:

[0127] Step S331: After step S32, the calibration data and are obtained. These calibration data will be applied to the control circuit of the display screen to correct the brightness and color deviation of the pixel;

[0128] The brightness and color calibration of each pixel can be adjusted in the following way:

[0129] ,

[0130] ,

[0131] where, is the calibrated brightness, is the calibrated color; These calibrated data will control the display effect of each pixel through the control circuit of the display screen;

[0132] Step S332: The real-time error feedback is adjusted by monitoring the display effect of the screen in real time and the error value calculated by error detection; The feedback mechanism is usually based on the PID control algorithm, aiming to adjust the calibration data according to the size and trend of the error to ensure the continuity and consistency of the display effect;

[0133] Assume that the error of the current display effect is , and the update of the calibration parameter can be expressed as:

[0134] ,

[0135] ,

[0136] Among them, , , are the proportional, integral, and derivative coefficients of the PID controller, is the current error, and are the new correction data; represents the integral term, represents the integral of the error from the initial time to the current time;

[0137] Based on the above feedback adjustment, the correction parameters can be continuously adjusted to keep the display screen in the best display effect during actual application.

[0138] Among them, the specific steps of step S4 are as follows:

[0139] Step S41: The brightness correction signal is achieved by adjusting the voltage or current of each pixel of the display screen; the brightness control signal is expressed as:

[0140] ,

[0141] Among them, is the brightness correction value of pixel i; is the maximum voltage that this pixel can reach; is the gamma value for brightness adjustment; represents a non-linear function;

[0142] The above formula indicates that by the brightness correction value adjust the voltage signal of this pixel to achieve the corrected brightness effect;

[0143] Step S42: Assume that the color of each pixel is determined by the current intensities of the RGB three channels. The color correction control signal is expressed as:

[0144] ,

[0145] Among them, is the color correction value of pixel i; is the maximum current that this pixel can reach; is the gamma value for color adjustment; represents a non-linear function;

[0146] The above formula indicates that by the color correction value , driving the current changes of the RGB three channels, thereby correcting the color of the pixel;

[0147] Step S43: Assume that the signal received by the driving circuit is a current signal and , and correspond to brightness and color respectively, then its drive control can be expressed as:

[0148] ,

[0149] ,

[0150] Among them, and are the gain coefficients of the driving circuit, corresponding to brightness and color adjustment respectively; and are the current signals finally input to each pixel of the display screen;

[0151] By adjusting these current signals, the brightness and color of each pixel of the display screen will be accurately corrected according to the correction value.

[0152] Among them, step S5 is specifically:

[0153] Monitoring the temperature and humidity values in the environment through a temperature sensor and a humidity sensor, and calculating the correction amount of each pixel by weighted synthesis of the influences of different environmental conditions;

[0154] ,

[0155] Among them,

[0156] and are the correction coefficients of the influence of temperature and humidity on brightness; represents the current actual brightness; represents the adjusted brightness after environmental compensation;

[0157] and are the change amounts of temperature and humidity respectively.

[0158] Application Example 1

[0159] This embodiment is applied to a large-size OLED screen (TV);

[0160] As shown in the appendix Figure 2 , it shows the changes in the display effect before and after implementation, especially in terms of brightness uniformity and color accuracy.

[0161] Brightness Uniformity: After calibration, the brightness uniformity of the display screen has been significantly improved. Especially in high-temperature and strong-light environments, the brightness difference of the display screen has been effectively reduced.

[0162] Color Accuracy: After calibration, the ΔE value has been significantly reduced, and the display effect is closer to the ideal standard, ensuring a more realistic color performance.

[0163] Stability: Through dynamic adaptive adjustment, the brightness and color stability of the display screen have been significantly enhanced under temperature changes and external light conditions.

[0164] Application Example 2

[0165] This embodiment is applied to a small-sized OLED screen (smartphone);

[0166] As shown in the appendix Figure 3 The following are the test data of the OLED screen in strong light and high-temperature environments, demonstrating the actual effect of the method of the present invention;

[0167] Brightness Enhancement: After dynamic calibration, the brightness of the display screen in strong light environments has increased by approximately 50%, ensuring that users can clearly view the screen content and greatly enhancing the outdoor usage experience.

[0168] Improved Color Accuracy: The ΔE value has been significantly reduced. Especially in strong light and low-temperature environments, the color performance tends to be ideal, and users can obtain a realistic color experience under various environmental conditions.

[0169] This specific embodiment is only an interpretation of the present invention and is not a limitation thereof. Those skilled in the art can make modifications to this embodiment without creative contributions according to their needs after reading this specification, but as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A high-precision pixel automatic correction method for a glass-based display screen, characterized in that , including the following steps: Step S1, data collection: by installing a high-precision sensor device on the surface or inner layer of the display screen, the brightness, color and position information of each pixel on the display screen is collected in real time, and the data is transmitted to the data processing system; Step S2, pixel point position and brightness mapping modeling; The data processing system receives the data and accurately models the brightness, color and position information of each pixel in the display screen, providing accurate data support for subsequent data correction and optimization; Step S3, error detection and correction data calculation; based on the pixel position and brightness mapping modeling, further data correction and optimization are performed; Step S4, pixel correction and control circuit implementation; the calculated correction data of each pixel is transmitted to the control circuit of the display screen, and the control circuit adjusts the driving current of the display screen according to the correction data, thereby realizing automatic correction of the brightness, color and position accuracy of the pixel points, ensuring that the display effect meets the expected standard; Step S5: Dynamic adaptive adjustment mechanism; During the display process, the environmental conditions of the display screen are monitored in real time, and the correction data is adjusted dynamically; The step S3 comprises: The least square method and nonlinear regression method are introduced to calculate the correction parameters; Among them, the implementation of the nonlinear regression method includes: The position of the pixel is located by the horizontal and vertical coordinates of the pixel, and then the relationship between the pixel brightness and position is represented based on a nonlinear model; The nonlinear model is fitted and optimized to obtain the optimal correction function to complete the correction; In the error detection process, it is necessary to traverse all pixels and calculate the brightness error and color error of each pixel; Specifically, it includes: calculating the brightness error and color error of each pixel point based on the brightness and color of the pixel point after the pixel point position and brightness mapping modeling step and the brightness and color under the ideal display standard; By counting and analyzing the distribution of errors, the pixels whose errors exceed the preset tolerance range are identified as target pixels that need to be corrected; Based on PID control algorithm, it aims to adjust the correction data according to the size and trend of the error; Specifically, it includes: inputting the error of the current display effect, adjusting the correction parameters based on the proportional, integral and differential coefficients of the PID controller in the PID control algorithm, so that the display screen always maintains the best display effect during the actual application process; the step S4 includes: Step S41: The brightness correction signal is realized by adjusting the voltage or current of each pixel of the display screen, and the brightness correction signal includes a gamma value for brightness adjustment.

2. The high-precision pixel automatic correction method for a glass-based display screen according to claim 1, characterized in that: The step S2 is specifically as follows: Step S21: After data collection is completed, the collected raw data must be preprocessed to provide more accurate input for subsequent pixel position and brightness mapping modeling; Step S22: After the data preprocessing is completed, the modeling stage of pixel position and brightness mapping is entered, the purpose of which is to convert the collected brightness and position data of each pixel into a mathematical model that can accurately represent the state of the display screen; Step S23: After constructing the pixel position and brightness mapping model, the display screen is calibrated using the model to optimize the brightness and position of each pixel to achieve a predetermined display effect.

3. The high-precision pixel automatic correction method for a glass-based display screen according to claim 2, characterized in that: The step S21 is specifically as follows: Step S211, smoothing the collected data by using a Gaussian filtering algorithm to remove the influence of noise existing in the data collection process on subsequent modeling, and retaining the main features of the data and removing random fluctuations by setting appropriate filtering parameters; Step S212: Different high-precision sensor devices and display screens with different screen sizes and resolutions will result in different ranges of collected data; by normalizing the brightness and color information of each pixel, the value range of the data is within a unified standard range; Step S212: perform outlier detection using a robust regression algorithm and remove abnormal data points to ensure the reliability of the final data set.

4. The high-precision pixel automatic correction method for a glass-based display screen according to claim 2, characterized in that: The Kalman filter algorithm is introduced in step S22. The Kalman filter algorithm combines the current error with the past state data through recursive calculation, thereby dynamically adjusting the mapping model to minimize the error and ensure the accuracy and stability of the model.

5. The high-precision pixel automatic correction method for a glass-based display screen according to claim 1, characterized in that: The step S3 is specifically as follows: Step S31, pixel error detection and identification: Step S32, correcting the pixel to be corrected at the identified location; Step S33: Real-time correction and feedback adjustment of pixels.

6. The high-precision pixel automatic correction method for a glass-based display screen according to claim 5, characterized in that: The step S31 is specifically as follows: Assume that the brightness and color of the pixels corrected by the pixel position and brightness mapping model are and , while the brightness and color under the ideal display standard are and , the following error formula is used to calculate the deviation of brightness and color: ， ， in, Indicates brightness error; Indicates color error; During the error detection process, it is first necessary to traverse all pixel points, calculate the brightness error and color error of each pixel point, and then identify which pixel points have errors exceeding the preset tolerance range through statistics and analysis of the error distribution, as the target pixels that need to be corrected.

7. A high-precision pixel automatic correction method for a glass-based display screen according to claim 6, characterized in that: The step S32 is specifically as follows: Step S321, calculating correction parameters based on the least square method and by minimizing the sum of squares of errors, so that the corrected brightness and color of each pixel point are close to the ideal value; Assume there are multiple pixels N, and the error of each pixel is determined by the brightness error and color error The objective function of the least squares method can be written as: ， By optimizing the above objective function, an optimal correction data set can be obtained and ; Step S322: On some display screens, the brightness and color errors of pixels may not be distributed linearly. In this case, a nonlinear regression method is needed to more accurately calculate the error correction value. Assume that the relationship between brightness error and position can be expressed by a nonlinear function: ， in, and Represents the horizontal and vertical coordinates of the pixel; It is a nonlinear function that represents the relationship between pixel brightness and position; is the error term; By fitting and optimizing the above nonlinear model, the optimal correction function is obtained. and use it to correct the brightness and color of the pixels.

8. The high-precision pixel automatic correction method for a glass-based display screen according to claim 7, characterized in that: The step S33 is specifically as follows: Step S331: After step S32, a calibration data set is obtained. and , these correction data will be applied to the control circuit of the display screen to correct the brightness and color deviation of the pixels; The brightness and color correction of each pixel can be adjusted by: ， ， in, is the corrected brightness, It is the corrected color; these corrected data will control the display effect of each pixel through the control circuit of the display screen; Step S332, real-time error feedback is adjusted by real-time monitoring of the screen display effect and the error value calculated by error detection; the feedback mechanism is usually based on the PID control algorithm, which aims to adjust the correction data according to the size and trend of the error to ensure the continuity and consistency of the display effect; Assume that the error of the current display effect is , the update of the correction parameters can be expressed as: ， ， in, , , are the proportional, integral and differential coefficients of the PID controller, is the current error, and is the new calibration data; represents the integral term, where Represents the integral of the error from the initial moment to the current moment; Based on the above feedback adjustment, the correction parameters can be continuously adjusted so that the display screen always maintains the best display effect during actual application.

9. The high-precision pixel automatic correction method for a glass-based display screen according to claim 1, characterized in that: The step S4 is specifically as follows: Step S41: The brightness correction signal is realized by adjusting the voltage or current of each pixel of the display screen; the brightness control signal It is expressed as: ， in, is the brightness correction value of pixel i; is the maximum voltage that the pixel can reach; Gamma value for brightness adjustment; represents a nonlinear function; The above formula shows that the brightness correction value Adjust the voltage signal of the pixel , to achieve the corrected brightness effect; Step S42: Assuming that the color of each pixel is determined by the current intensity of the three channels RGB, the color correction control signal It is expressed as: ， in, is the color correction value of pixel i; is the maximum current that the pixel can reach; Gamma value for color adjustment; represents a nonlinear function; The above formula indicates that the color correction value , driving the current changes of the three channels of RGB, thereby correcting the color of the pixel; Step S43: Assume that the signal received by the driving circuit is a current signal and , and Corresponding to brightness and color respectively, the drive control can be expressed as: ， ， in, and is the gain coefficient of the driving circuit, corresponding to brightness and color adjustment respectively; and It is the current signal that is ultimately input to each pixel of the display; By adjusting these current signals, the brightness and color of each pixel of the display will be precisely corrected according to the calibration values.

10. The high-precision pixel automatic correction method for a glass-based display screen according to claim 1, characterized in that: The step S5 is specifically as follows: The temperature and humidity values ​​in the environment are monitored by temperature sensors and humidity sensors, and the correction value of each pixel is calculated by weighted synthesis of the influence of different environmental conditions; ， in, and is the correction factor for the effect of temperature and humidity on brightness; Indicates the current actual brightness; Indicates the adjusted brightness after environmental compensation; and are the changes in temperature and humidity respectively.

Images