CN118411932B

CN118411932B - LED display screen brightness correction method and correction system thereof

Info

Publication number: CN118411932B
Application number: CN202410676523.1A
Authority: CN
Inventors: 陈国华
Original assignee: Shenzhen Cress Zhixian Technology Co ltd
Current assignee: Shenzhen Cress Zhixian Technology Co ltd
Priority date: 2024-05-29
Filing date: 2024-05-29
Publication date: 2024-10-01
Anticipated expiration: 2044-05-29
Also published as: CN118411932A

Abstract

The invention relates to the technical field of brightness correction, in particular to a brightness correction method and a brightness correction system for an LED display screen. The method comprises the following steps: carrying out brightness level sensing analysis and brightness cluster analysis on each pixel point in the LED display screen through the built-in camera and the brightness sensing sensor to obtain a similar cluster of the brightness level of the LED pixel point; carrying out pixel space optimization conversion and reconstruction distance calculation on each pixel point in the LED pixel point brightness level similar clusters to obtain reconstruction distance values among the reconstruction space points of each similar pixel; carrying out area connection division on each pixel point in the LED pixel point brightness level similar clusters to obtain brightness level similar pixel connection sub-areas; and carrying out chromaticity evaluation analysis and brightness deviation correction analysis on the similar pixel connection subareas of the brightness level so as to obtain a correction result of the brightness deviation of the LED display. The invention can realize the balance of the brightness and the chromaticity of the LED display screen.

Description

LED display screen brightness correction method and correction system thereof

Technical Field

The invention relates to the technical field of brightness correction, in particular to a brightness correction method and a brightness correction system for an LED display screen.

Background

The LED display screen is widely applied to display equipment in the fields of indoor and outdoor advertisements, stage performances, information release and the like, the brightness and color accuracy of the LED display screen is critical to the display effect, and meanwhile, due to factors such as long-term use, environmental change and the like of the LED display screen, the brightness and the color of the LED display screen drift or are uneven, so that the display effect and the look and feel of the LED display screen are affected. However, the conventional method for correcting the brightness and the chrominance of the LED display screen is generally based on manual adjustment or a simple correction algorithm, and has the problems of poor correction effect and low brightness monitoring precision.

Disclosure of Invention

Accordingly, the present invention is directed to a method and a system for correcting brightness and color of an LED display screen, so as to solve at least one of the above-mentioned problems.

In order to achieve the above purpose, a brightness correction method for an LED display screen includes the following steps:

Step S1: carrying out brightness level perception analysis on each pixel point in the LED display screen through a camera and a brightness perception sensor which are arranged in the LED display screen so as to obtain LED brightness level data of each pixel point; performing brightness cluster analysis on the LED brightness level data of each pixel point to obtain an LED pixel point brightness level similar cluster;

Step S2: performing pixel space optimization conversion on each pixel point in the LED pixel point brightness level similar clusters to obtain a brightness level similar pixel reconstruction space point set; performing reconstruction distance calculation on the similar pixel reconstruction space point set of the brightness level to obtain a reconstruction distance value between the similar pixel reconstruction space points;

Step S3: carrying out area connection division on each pixel point in the LED pixel point brightness level similar cluster based on the reconstruction distance value between the reconstruction space points of each similar pixel to obtain a brightness level similar pixel connection sub-area; performing chromaticity evaluation analysis on the similar pixel connection subareas of the brightness level to obtain the average chromaticity of the LEDs of the similar pixel subareas;

Step S4: and carrying out brightness deviation correction analysis on the similar pixel connection subareas of the brightness level based on the average chromaticity of the LEDs in the similar pixel subareas so as to obtain the correction result of the brightness deviation of the LED display.

According to the invention, the LED display screen is subjected to illumination scanning treatment by using the camera arranged in the LED display screen, and the key of the step is that the camera is utilized to acquire the real-time illumination condition of the surface of the display screen, so that the illumination distribution condition and the changed image of the LED display screen can be captured, and the basic data guarantee is provided for subsequent analysis and treatment. Meanwhile, the brightness level perception sensor arranged inside the LED display screen is used for carrying out brightness level perception analysis on the LED display screen illumination image of each pixel point, the analysis can acquire the actual brightness level of each pixel point by using the sensor, so that the brightness condition of each area of the LED display screen is quantized and recorded, key data can be provided for brightness optimization and calibration of the LED display screen through the brightness level perception analysis, the stability and consistency of the display effect are ensured, and the monitoring precision and accuracy of the brightness uneven area can be improved. through carrying out brightness cluster analysis on the LED brightness level data of each pixel point, the step carries out cluster analysis on each pixel point of the LED display screen according to the brightness level of the pixel point, so that cluster clusters with different brightness levels are identified, the overall brightness distribution condition of the LED display screen is further understood, potential brightness abnormality or non-uniformity problems are found, and corresponding calibration measures are adopted, so that the overall display quality and user experience are improved. Secondly, through carrying out pixel space point mapping conversion on each pixel point in the LED pixel point brightness level similar clusters, the key of the step is that the pixel points in the similar clusters can be mapped and converted according to the brightness levels of the pixel points, so that an initial pixel space point set is created, basic data is provided for subsequent feature analysis and reconstruction optimization by the set, and a foundation is laid for further image processing and optimization. The texture characteristics and the edge characteristics of each pixel point in the same type of clusters of the brightness levels of the LED pixel points are analyzed, and the initial space point set converted by mapping is optimized and reconstructed so as to improve the structure and quality of the pixel space. By calculating the reconstruction distance of the pixel reconstruction space point set of the same type of brightness level, the effect and quality of pixel space reconstruction can be evaluated by calculating the reconstruction distance, so that an optimal pixel reconstruction scheme is determined, data support is provided for the subsequent pixel sub-region connection process by the distance values, and basic data guarantee is further provided for the subsequent chromaticity evaluation analysis. and then, comparing and judging the reconstruction distance value among the reconstruction space points of the similar pixels by using a preset reconstruction distance standard value to divide similar adjacent pixel point sets and similar remote pixel point sets, wherein the step can accurately divide the adjacent relationship and the remote relationship among the similar pixels by an effective distance standard judging mechanism until the corresponding pixel points in the similar remote pixel point sets are divided into adjacent point sets, thereby laying a basic data guarantee for the subsequent region connection processing process. The main purpose of the step is to aggregate similar pixels into continuous areas according to the proximity relation by carrying out area connection division on the similar proximity point set of each brightness level to form larger similar pixel subareas, and the relevance and consistency of each part in the pixel space can be better identified by the area connection division, so that an accurate data basis is provided for subsequent chromaticity evaluation and analysis. In addition, by carrying out chromaticity evaluation analysis on the similar pixel connection subareas of the brightness level, the average chromaticity of the subareas can be effectively measured and calculated by carrying out evaluation analysis on the color characteristics of each connection subarea, so that the color distribution and consistency of different areas in the pixel space are further analyzed, and the optimal effect of the pixel space on color expression is ensured. Finally, through carrying out luminance difference evaluation analysis on the same-type pixel connection subareas with different luminance levels and carrying out chromaticity difference evaluation analysis on the same-type pixel connection subareas with different luminance levels based on the average chromaticity of the LEDs of the same-type pixel subareas, the luminance difference factors and the chromaticity difference factors among different areas can be obtained, and meanwhile, through carrying out luminance difference statistical analysis on the same-type pixel connection subareas with luminance levels based on the luminance difference factors and the chromaticity difference factors, the luminance difference coefficient of each area is quantized by comprehensively considering the luminance and chromaticity differences, and the coefficient can help to determine which areas need to be adjusted to achieve more uniform luminance and color representation. In addition, a corresponding current driving correction strategy is formulated according to the quantized brightness deviation degree coefficient, and comprises the steps of increasing or reducing current driving of the LED lamps in the LED display screen, so that the brightness of different areas of the LED display screen can be adjusted to be more uniform, the brightness correction effect of the LED display screen is improved, and the LED display screen can display accurate, bright colors and bright pictures.

Preferably, the present invention further provides an LED display screen brightness and color correction system for performing the LED display screen brightness and color correction method as described above, the LED display screen brightness and color correction system comprising:

The brightness level perception cluster analysis module is used for carrying out brightness level perception analysis on each pixel point in the LED display screen through a camera and a brightness perception sensor which are arranged in the LED display screen so as to obtain LED brightness level data of each pixel point; performing brightness cluster analysis on the LED brightness level data of each pixel point to obtain an LED pixel point brightness level similar cluster;

The brightness level pixel point reconstruction distance quantization module is used for carrying out pixel space optimization conversion on each pixel point in the LED pixel point brightness level similar clusters so as to obtain a brightness level similar pixel reconstruction space point set; performing reconstruction distance calculation on the similar pixel reconstruction space point set of the brightness level, so as to obtain a reconstruction distance value between the similar pixel reconstruction space points;

The similar pixel sub-region chromaticity evaluation module is used for carrying out region connection division on each pixel point in the similar clusters of the brightness level of the LED pixel points based on the reconstruction distance values among the reconstruction space points of the similar pixels so as to obtain similar pixel connection sub-regions of the brightness level; performing chromaticity evaluation analysis on the similar pixel connection subareas of the brightness level so as to obtain the average chromaticity of the LEDs of the similar pixel subareas;

the display brightness deviation correction module is used for carrying out brightness deviation correction analysis on the similar pixel connection subareas of the brightness level based on the average chromaticity of the LEDs in the similar pixel subareas so as to obtain the correction result of the brightness deviation of the LEDs.

In summary, the invention provides a brightness correction system for an LED display screen, which is composed of a brightness level sensing cluster analysis module, a brightness level pixel reconstruction distance quantization module and a display brightness deviation correction module, so that the brightness correction method for an LED display screen can be implemented, any one of the brightness correction methods for the LED display screen can be implemented by combining the operation of computer programs running on each module, and the internal structures of the systems cooperate with each other, thus greatly reducing the repeated work and labor investment, and providing a more accurate and efficient brightness correction process for the LED display screen quickly and effectively, thereby simplifying the operation flow of the brightness correction system for the LED display screen.

Drawings

Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of a non-limiting implementation, made with reference to the accompanying drawings in which:

FIG. 1 is a schematic flow chart of steps of a method for correcting brightness and color of an LED display screen according to the present invention;

FIG. 2 is a detailed step flow chart of step S1 in FIG. 1;

Fig. 3 is a detailed step flow chart of step S2 in fig. 1.

Detailed Description

The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.

Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.

It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.

In order to achieve the above objective, referring to fig. 1 to 3, the present invention provides a method for correcting brightness and color of an LED display screen, the method comprising the following steps:

In the embodiment of the present invention, please refer to fig. 1, which is a schematic flow chart of steps of the method for correcting brightness and color of an LED display screen, in this example, the method for correcting brightness and color of an LED display screen includes the following steps:

According to the embodiment of the invention, the camera arranged in the LED display screen is used for scanning the surface illumination condition in the LED display screen in a progressive scanning or progressive scanning mode so as to obtain the real-time illumination image of the surface of the display screen, the scanned illumination image of the LED display screen is divided by using a pixel-level region growing and dividing algorithm so as to divide the corresponding image into a plurality of pixel regions, each region corresponds to one pixel point of the LED display screen, and meanwhile, the brightness level perception analysis is carried out on the LED display screen illumination image of each divided pixel point by using the brightness perception sensor arranged in the LED display screen so as to perceive and collect the illumination intensity or brightness value at each pixel point, thereby obtaining the LED brightness level data of each pixel point. Then, the LED brightness level data of each pixel point is subjected to clustering analysis by using a corresponding clustering algorithm (such as K-means clustering, gaussian mixture model and the like) so as to divide the pixel point into a plurality of similar clusters according to the brightness level of the pixel point, and finally the similar clusters of the brightness level of the LED pixel point are obtained.

According to the embodiment of the invention, the mapping conversion of the space points is carried out on each pixel point in the LED pixel point brightness level similar clusters by using the operations such as coordinate system conversion, pixel position adjustment or geometric conversion and the like, so that the pixel points in the similar clusters are mapped into a unified space coordinate system according to the brightness levels of the pixel points, wherein an x-axis represents the horizontal position of the pixel points in the image coordinate system, a y-axis represents the vertical position of the pixel points in the image coordinate system, a z-axis represents the brightness level value of the pixel points, and the corresponding feature analysis technology (such as a local binary mode, a Gaussian filter and the like and Sobel, canny and the like) is used for carrying out feature analysis on each pixel point in the LED pixel point brightness level similar clusters, so that the texture feature information and the edge feature information of each pixel point are extracted, and the pixel edge feature obtained through combination analysis are carried out on the change condition of the feature at each pixel point in the pixel space initial point set obtained through the mapping, the texture adjustment and the feature optimization are carried out on the pixel point brightness level, the pixel brightness level distribution and the pixel space level is improved, and the similar pixel brightness space is improved, and the similar brightness level distribution is improved. And then, calculating the reconstruction distance of the similar pixel reconstruction space point set of the brightness level by using a proper pixel reconstruction distance calculation formula so as to quantitatively calculate the reconstruction distance condition among the space points to evaluate the distance relation among the similar pixel points, and finally obtaining the reconstruction distance value among the similar pixel reconstruction space points.

The embodiment of the invention compares and judges the reconstruction distance value between the reconstruction space points of each similar pixel obtained by the previous quantization calculation by using a preset reconstruction distance standard value, and if the reconstruction distance value between any two similar pixel reconstruction space points is smaller than the preset reconstruction distance standard value, the reconstruction distance value is divided into similar adjacent pixel points with the brightness level; if the reconstruction distance value between any two similar pixel reconstruction space points is larger than or equal to a preset reconstruction distance standard value, dividing the reconstruction distance value into similar remote pixel points with the brightness level. Meanwhile, checking the relation between each pixel point in the LED pixel point brightness level similar clusters and any other pixel point, if judging that the adjacent pixel points which are similar to each other and the brightness level similar to each other exist, classifying the adjacent pixel points into a point set, and indicating that the corresponding pixel points are in a nearby range, thereby obtaining similar adjacent point sets; if the same type of remote pixel points with the brightness level as any other pixel points are judged to be obtained, the same type of remote pixel points are also classified into a point set, and the fact that the corresponding pixel points are not in the nearby range or deviate from the corresponding limit area is indicated, so that the same type of remote point set is obtained. Secondly, resetting the corresponding reconstruction distance standard value (increasing or decreasing) to compare and judge the reconstruction distance value between each pixel point in the corresponding similar remote point set again, dividing the similar remote point set into another adjacent point set and remote point set in the opposite remote area through the previous comparison and judgment rule, and the like until the pixel points in the similar remote point set with the brightness level are zero, and stopping iteration; otherwise, the steps are repeated. And the pixel points in the similar adjacent point sets obtained by each classification are subjected to area connection so as to aggregate similar pixel points into continuous areas according to the adjacent relation to form larger similar pixel sub-areas, thereby obtaining the brightness level similar pixel connection sub-areas. And finally, carrying out average analysis on the pixel chromaticity at each pixel point by using an arithmetic average statistical method so as to statistically calculate the average value of the chromaticity values of all the pixel points in the corresponding sub-region, representing the overall color characteristics of the sub-region, and finally obtaining the average chromaticity of the LEDs of the similar pixel sub-region.

According to the embodiment of the invention, each brightness level similar pixel connection subarea is divided into a plurality of groups of different types of pixel subareas according to different types, each group comprises pixel connection subareas with similar brightness level characteristics, a proper brightness difference evaluation method (such as mean square error, brightness histogram difference and the like) is used for carrying out difference evaluation analysis on brightness levels among the different types of brightness level similar pixel connection subareas so as to evaluate and calculate brightness difference factors among the different groups of pixel connection subareas, a proper chromaticity difference evaluation method (such as chromaticity histogram comparison, chromaticity distance calculation and the like) is used for carrying out difference evaluation analysis on chromaticity levels among the different types of brightness level similar pixel connection subareas according to the obtained through the combination analysis, so as to evaluate and calculate the chromaticity difference factors among the different types of brightness level similar pixel connection subareas, a deviation statistical analysis method (such as mean value, standard difference, correlation coefficient and the like) is used for carrying out chromaticity difference analysis on the corresponding brightness levels among the corresponding brightness level similar pixel connection subareas so as to comprehensively consider brightness and chromaticity difference coefficients, a threshold value is set for calculating the brightness difference coefficient of the brightness difference coefficient, and a threshold value is set for the brightness difference coefficient is calculated if the brightness difference coefficient is smaller than the threshold value is smaller than the brightness coefficient of the brightness difference coefficient is set for the brightness difference, if the brightness deviation degree coefficient is larger than or equal to a preset brightness deviation degree threshold value, the pixel subareas corresponding to the brightness deviation degree coefficient are indicated to have large brightness deviation, corresponding current driving correction is carried out on the pixel subareas so as to adjust current driving parameters of LEDs in the corresponding areas, for example, current driving of LED lamps in an LED display screen is increased or reduced, deviation between brightness and chromaticity of the LED display screen is reduced, and the display effect of the corrected LED display screen subareas is ensured to be more uniform and consistent, and finally, the LED display brightness deviation correction result is obtained.

Preferably, step S1 comprises the steps of:

step S11: carrying out surface illumination scanning treatment on the LED display screen through a camera arranged in the LED display screen to obtain an illumination image on the surface of the LED display screen;

step S12: performing contrast enhancement processing on the illumination image on the surface of the LED display screen to obtain an illumination contrast enhancement image of the LED display screen;

Step S13: performing pixel level division processing on the LED display screen illumination contrast enhancement image to obtain an LED display screen illumination image of each pixel point;

step S14: performing brightness level sensing analysis on the LED display screen illumination image of each pixel point through a brightness sensing sensor arranged in the LED display screen to obtain LED brightness level data of each pixel point;

step S15: and carrying out brightness cluster analysis on the LED brightness level data of each pixel point to obtain the similar clusters of the LED pixel point brightness level.

As an embodiment of the present invention, referring to fig. 2, a detailed step flow chart of step S1 in fig. 1 is shown, in which step S1 includes the following steps:

According to the embodiment of the invention, the camera arranged in the LED display screen is used for scanning the surface illumination condition in the LED display screen in a progressive scanning or progressive scanning mode, so that the real-time illumination image of the surface of the display screen is obtained, the distribution condition and the change of the illumination of the LED display screen are captured, and finally the surface illumination image of the LED display screen is obtained.

According to the embodiment of the invention, the contrast enhancement treatment is carried out on the illumination image on the surface of the LED display screen by using methods such as histogram equalization, contrast stretching and the like, so that the contrast of the illumination image is enhanced to improve the definition and the readability of illumination information in the image, and finally the illumination contrast enhancement image of the LED display screen is obtained.

According to the embodiment of the invention, the LED display screen illumination contrast enhancement image after contrast enhancement is divided by using a pixel-level region growth segmentation algorithm, so that the corresponding image is segmented into a plurality of pixel regions, each region corresponds to one pixel point of the LED display screen, and therefore, the illumination image is segmented into the image with the pixel level, the illumination condition of each pixel point is embodied and independently analyzed, and finally, the LED display screen illumination image of each pixel point is obtained.

According to the embodiment of the invention, the brightness level sensing sensor arranged in the LED display screen is used for performing the sensing analysis of the brightness level on the LED display screen illumination image of each divided pixel point so as to sense and collect the illumination intensity or brightness value of each pixel point, and finally the LED brightness level data of each pixel point is obtained.

According to the embodiment of the invention, the LED brightness level data of each pixel point is subjected to cluster analysis by using a corresponding clustering algorithm (such as K-means clustering, gaussian mixture model and the like) so as to divide the pixel point into a plurality of similar clusters according to the brightness level of the pixel point, and finally the similar clusters of the brightness level of the LED pixel point are obtained.

According to the invention, the camera arranged in the LED display screen is used for carrying out surface illumination scanning treatment on the LED display screen, and the key of the step is that the camera is used for acquiring real-time illumination conditions of the surface of the display screen, so that the distribution conditions and changes of illumination of the LED display screen can be captured, and basic data guarantee is provided for subsequent analysis and treatment. And secondly, the illumination change and the area can be displayed more clearly by carrying out contrast enhancement processing on the illumination image on the surface of the LED display screen, so that the brightness level of each area is accurately analyzed, the subsequent pixel level division and brightness level perception analysis are facilitated, and the analysis precision and accuracy of the illumination condition of the display screen are improved. Then, through carrying out pixel level division processing on the LED display screen illumination contrast enhancement image, the step can divide the illumination image into images with pixel levels, so that the illumination condition of each pixel point can be embodied and independently analyzed, basic data is provided for the next brightness level perception analysis, and the comprehensive grasp of the illumination condition of each pixel point is ensured. And then, carrying out brightness level perception analysis on the LED display screen illumination image of each pixel point by using a brightness perception sensor arranged inside the LED display screen, wherein the analysis can obtain the actual brightness level of each pixel point by using the sensor, so as to quantify and record the brightness condition of each area of the LED display screen, and the brightness level perception analysis provides key data for optimizing and calibrating the brightness of the LED display screen and ensures the stability and consistency of the display effect of the LED display screen. Finally, through carrying out brightness cluster analysis on the LED brightness level data of each pixel point, the step carries out cluster analysis on each pixel point of the LED display screen according to the brightness level of the pixel point, so that cluster clusters with different brightness levels are identified, the overall brightness distribution condition of the LED display screen is further understood, potential brightness abnormality or non-uniformity problems are found, and corresponding calibration measures are adopted, so that the overall display quality and user experience are improved.

Preferably, step S2 comprises the steps of:

Step S21: performing pixel space point mapping conversion on each pixel point in the LED pixel point brightness level similar clusters to obtain a brightness level similar pixel space initial point set;

step S22: carrying out pixel texture feature analysis on each pixel point in the LED pixel point brightness level similar clusters to obtain pixel texture feature data of each pixel point in the brightness level similar clusters;

step S23: carrying out pixel edge characteristic analysis on each pixel point in the LED pixel point brightness level similar clusters to obtain pixel edge characteristic data of each pixel point in the brightness level similar clusters;

Step S24: performing pixel reconstruction optimization analysis on the initial point set of the pixel space of the same type of brightness level based on the pixel texture characteristic data and the pixel edge characteristic data of each pixel point in the same type of brightness level cluster to obtain the reconstructed spatial point set of the pixel of the same type of brightness level;

Step S25: and (3) calculating the reconstruction distance of the pixel reconstruction space point set of the same type of the brightness level by using a pixel reconstruction distance calculation formula to obtain the reconstruction distance value between the reconstruction space points of each same type of pixel.

As an embodiment of the present invention, referring to fig. 3, a detailed step flow chart of step S2 in fig. 1 is shown, in which step S2 includes the following steps:

According to the embodiment of the invention, the mapping conversion of the space points is carried out on each pixel point in the LED pixel point brightness level similar clusters by using the operations such as coordinate system conversion, pixel position adjustment or geometric conversion and the like, so that the pixel points in the similar clusters are mapped into a unified space coordinate system according to the brightness levels of the pixel points, wherein an x-axis represents the horizontal position of the pixel point in the image coordinate system, a y-axis represents the vertical position of the pixel point in the image coordinate system, a z-axis represents the brightness level value of the pixel point, and finally the initial point set of the pixel space of the brightness level similar is obtained.

according to the embodiment of the invention, texture feature analysis technology (such as a local binary pattern, a Gaussian filter and the like) is used for carrying out texture feature analysis on each pixel point in the LED pixel point brightness level similar cluster so as to extract texture feature information of each pixel point, including texture direction, texture density, texture contrast and the like, and the texture difference and similarity among the pixel points in the similar cluster are revealed, so that the pixel texture feature data of each pixel point in the brightness level similar cluster is finally obtained.

according to the embodiment of the invention, edge characteristic analysis is carried out on each pixel point in the LED pixel point brightness level similar clusters by using an edge detection algorithm (such as Sobel, canny and the like) so as to extract edge characteristic information of each pixel point, including information of edge intensity, edge direction, edge length and the like, and the edge structures and edge distribution conditions in different pixel points are identified, so that the pixel edge characteristic data of each pixel point in the brightness level similar clusters is finally obtained.

According to the embodiment of the invention, the pixel texture characteristic data and the pixel edge characteristic data of each pixel point in the brightness level similar clusters are obtained through combination analysis, reconstruction adjustment optimization is carried out on the detail change condition of the characteristics at each pixel space point in the brightness level similar pixel space initial point set, so that the texture and the edge characteristics of the pixels are considered, the space distribution of the brightness level similar pixels is optimized, the quality of pixel space point reconstruction is improved, and finally the brightness level similar pixel reconstruction space point set is obtained.

According to the embodiment of the invention, a proper pixel reconstruction distance calculation formula is formed by combining the term index parameters, the brightness values, the brightness weight coefficients, the pixel gradient values, the pixel gradient weight coefficients, the pixel texture characteristic values, the pixel texture characteristic weight coefficients, the pixel edge characteristic values, the pixel edge characteristic weight coefficients and the related parameters of the similar pixel reconstruction space points, so that the reconstruction distance calculation is carried out on the brightness level similar pixel reconstruction space point set, the reconstruction distance conditions among all the space points are calculated in a quantification mode, the distance relation among the similar pixel points is evaluated, and finally the reconstruction distance values among all the similar pixel reconstruction space points are obtained.

The invention firstly carries out pixel space point mapping conversion on each pixel point in the LED pixel point brightness level similar clusters, and the key of the step is that the pixel points in the similar clusters can be mapped and converted according to the brightness levels of the pixel points, so that an initial pixel space point set is created, the set provides basic data for subsequent feature analysis and reconstruction optimization, and a foundation is laid for further image processing and optimization. And secondly, by carrying out pixel texture feature analysis on each pixel point in the LED pixel point brightness level similar clusters, the texture difference and the similarity between the pixel points in the similar clusters can be revealed, further the understanding of the structure and the composition of an image is facilitated, and the feature data provides important clues for the subsequent pixel reconstruction optimization, thereby being beneficial to improving the quality and the definition of a pixel space. Then, by carrying out pixel edge feature analysis on each pixel point in the LED pixel point brightness level similar clusters, the edge structure and the edge distribution condition in the image can be identified, an important basis is provided for subsequent pixel reconstruction optimization, and the edge feature data are helpful for improving the definition and the identification degree of the pixel space, so that the quality of the display effect is improved. And then, carrying out pixel reconstruction optimization analysis on the initial point set of the pixel space of the same type of brightness level based on the pixel texture characteristic data and the pixel edge characteristic data of each pixel point in the same type of brightness level cluster, wherein the step combines the texture characteristic and the edge characteristic, and carries out optimization reconstruction on the initial point set so as to improve the structure and the quality of the pixel space. And finally, calculating a reconstruction distance of the pixel reconstruction space point set of the same type with the brightness level by using a proper pixel reconstruction distance calculation formula, wherein the effect and quality of pixel space reconstruction can be evaluated by calculating the reconstruction distance, so that an optimal pixel reconstruction scheme is determined, and the distance values provide data support for the subsequent pixel sub-region connection process and further provide basic data guarantee for the subsequent chromaticity evaluation analysis.

Preferably, step S24 comprises the steps of:

Step S241: performing pixel texture reconstruction optimization on the initial point set of the pixel space of the same type of brightness level based on the pixel texture characteristic data of each pixel point in the same type of brightness level cluster to obtain a reconstructed spatial point set of the same type of pixel texture;

According to the embodiment of the invention, the detail change condition of the texture feature at each pixel space point in the initial point set of the pixel space of the same brightness level is subjected to reconstruction adjustment optimization by combining the pixel texture feature data of each pixel point in the similar brightness level cluster obtained through analysis, so that the texture difference and the similarity between the pixel space points in the similar cluster are identified to purposefully adjust the texture attribute of the optimized pixel space point, and finally the similar pixel texture reconstruction space point set is obtained.

Step S242: carrying out pixel edge reconstruction optimization on the similar pixel texture reconstruction space point set based on pixel edge characteristic data of each pixel point in the similar cluster of the brightness level to obtain a similar pixel edge reconstruction space point set;

The embodiment of the invention also carries out reconstruction adjustment optimization on the detail change condition of the edge characteristic at each pixel space point in the similar pixel texture reconstruction space point set by combining the pixel edge characteristic data of each pixel point in the similar brightness level cluster obtained by analysis so as to accurately identify the edge structure and the edge distribution condition among similar pixels, and carries out optimization adjustment on the pixel edges according to the edge structure and the edge distribution condition, so that the edge lines of the pixel space are clearer and more natural, and finally the similar pixel edge reconstruction space point set is obtained.

Step S243: and carrying out smoothing treatment on the similar pixel edge reconstruction space point set to obtain the brightness level similar pixel reconstruction space point set.

According to the embodiment of the invention, each pixel space point in the similar pixel edge reconstruction space point set is subjected to smoothing treatment by using a smoothing filter or other smoothing technology, so that saw teeth and flaws generated by texture and edge optimization are eliminated, the transition of the pixel space is more natural and smooth, the obtained pixel space point set is ensured to have continuity and consistency in vision, and finally the brightness level similar pixel reconstruction space point set is obtained.

According to the invention, firstly, pixel texture reconstruction optimization is carried out on the initial point set of the pixel space of the same type of brightness level based on the pixel texture feature data of each pixel point in the same type of brightness level cluster, which means that the texture difference and the similarity between pixels in the same type of cluster can be identified by analyzing the texture feature of each pixel point, so that the texture attribute of the pixels can be adjusted in a targeted manner, and the pixels are more in line with the expected texture feature. Through the optimization, a similar pixel texture reconstruction space point set can be obtained, and each pixel point is carefully adjusted, so that the overall texture quality is improved, and the detail expression and the sense of reality of a pixel space are further improved. Then, the pixel edge reconstruction optimization is carried out on the pixel edge feature data of each pixel point in the similar clusters based on the brightness level, and the key of the step is that the edge feature data of the pixel points is utilized to accurately identify the edge structure and the edge distribution condition among similar pixels, and the optimization adjustment of the pixel edges is carried out according to the edge structure and the edge distribution condition. Finally, by carrying out smoothing treatment on the similar pixel edge reconstruction space point set, the aim of the step is to further optimize and perfect the whole effect of the pixel space, and by carrying out smoothing treatment on the pixel edge reconstruction space point set, saw teeth and flaws generated by edge optimization can be eliminated, so that the transition of the pixel space is more natural and smooth, and by the smoothing treatment, the similar pixel reconstruction space point set with the brightness level is finally obtained, and each pixel point is subjected to fine adjustment and smoothing treatment, so that the visual effect of the whole pixel space is more consistent and smooth, and the visual experience of a user is improved.

Preferably, the pixel reconstruction distance calculation formula in step S25 is specifically:

Wherein D (p, q) is a reconstruction distance value between a p-th similar pixel reconstruction space point and a q-th similar pixel reconstruction space point, p, q are each a term index parameter of a similar pixel reconstruction space point in a brightness level similar pixel reconstruction space point set, I _p is a brightness value at the p-th similar pixel reconstruction space point, I _q is a brightness value at the q-th similar pixel reconstruction space point, alpha is a brightness weight coefficient, Pixel gradient values at spatial points are reconstructed for the p-th homogeneous pixel,For the pixel gradient value at the q-th similar pixel reconstruction space point, β is a pixel gradient weight coefficient, T _p is a pixel texture feature value at the p-th similar pixel reconstruction space point, T _q is a pixel texture feature value at the q-th similar pixel reconstruction space point, γ is a pixel texture feature weight coefficient, B _p is a pixel edge feature value at the p-th similar pixel reconstruction space point, B _q is a pixel edge feature value at the q-th similar pixel reconstruction space point, δ is a pixel edge feature weight coefficient, and η is a correction coefficient of the reconstruction distance value.

According to the invention, a specific mathematical model is used and verified to obtain a pixel reconstruction distance calculation formula, which is used for calculating the reconstruction distance of the pixel reconstruction space point set of the same type of brightness level, the pixel reconstruction distance calculation formula considers four different pixel characteristics of brightness, pixel gradient, texture characteristics and edge characteristics, the comprehensive consideration can describe the difference among pixels more comprehensively, and the capturing of fine change among pixels is facilitated, so that the reconstruction distance is calculated more accurately. The alpha, beta, gamma and delta in the formula are used for adjusting the weights of different features in the distance calculation, and the influence degree of the different features on the distance calculation can be different by adjusting the weight coefficients, so that the method is better suitable for actual conditions. In addition, the formula can be adjusted according to actual conditions by introducing correction coefficients so as to improve the accuracy and applicability of distance calculation. By calculating the reconstruction distance, the similarity measurement between the similar pixel reconstruction space points can be obtained, and the measurement can help to identify the pixel points with higher similarity in the pixel reconstruction process, so that the pixel reconstruction optimization analysis is better carried out. In summary, the pixel reconstruction distance calculation formula considers various pixel characteristics, and improves the accuracy and applicability of calculation in the modes of weight adjustment, correction coefficient and the like, thereby providing an important basis for subsequent pixel reconstruction optimization analysis. Therefore, the formula can fully consider the reconstruction distance value D (p, q) between the p-th similar pixel reconstruction space point and the q-th similar pixel reconstruction space point, the term index parameters p, q of the similar pixel reconstruction space points in the brightness level similar pixel reconstruction space point set, the brightness value I _p at the p-th similar pixel reconstruction space point, the brightness value I _q at the q-th similar pixel reconstruction space point, the brightness weight coefficient alpha and the pixel gradient value at the p-th similar pixel reconstruction space pointReconstructing pixel gradient values at spatial points for the q-th homogeneous pixelThe pixel gradient weight coefficient beta, the pixel texture characteristic value T _p at the p-th similar pixel reconstruction space point, the pixel texture characteristic value T _q at the q-th similar pixel reconstruction space point, the pixel texture characteristic weight coefficient gamma, the pixel edge characteristic value B _p at the p-th similar pixel reconstruction space point, the pixel edge characteristic value B _q at the q-th similar pixel reconstruction space point, the pixel edge characteristic weight coefficient delta, the correction coefficient eta of the reconstruction distance value, and a functional relation is formed according to the correlation relation between the reconstruction distance value D (p, q) between the p-th similar pixel reconstruction space point and the q-th similar pixel reconstruction space point and the parameters:

The formula can realize the calculation process of the reconstruction distance of the pixel reconstruction space point set with the same brightness level, and can be adjusted according to the error condition in the calculation process by introducing the correction coefficient eta of the reconstruction distance value, thereby improving the accuracy and the applicability of the calculation formula of the pixel reconstruction distance.

Preferably, step S3 comprises the steps of:

Step S31: comparing and judging the reconstruction distance values among the reconstruction space points of the same-type pixels according to a preset reconstruction distance standard value, and marking the pixels corresponding to the same-type clusters with the brightness levels of the LED pixels as similar adjacent pixels with the brightness levels when the reconstruction distance values among any two similar-type pixels are smaller than the preset reconstruction distance standard value; when the reconstruction distance value between any two similar pixel reconstruction space points is larger than or equal to a preset reconstruction distance standard value, marking the corresponding pixel points in the LED pixel point brightness level similar clusters as similar remote pixel points with the brightness level;

The embodiment of the invention compares and judges the reconstruction distance value between the reconstruction space points of each similar pixel obtained by the previous quantization calculation by using a preset reconstruction distance standard value, and if the reconstruction distance value between any two similar pixel reconstruction space points is smaller than the preset reconstruction distance standard value, the distance between the corresponding two similar pixel reconstruction space points is relatively close, and the two corresponding pixel points in the LED pixel point brightness level similar cluster are marked as brightness level similar adjacent pixel points; if the reconstruction distance value between any two similar pixel reconstruction space points is larger than or equal to a preset reconstruction distance standard value, which indicates that the distance between the corresponding two similar pixel reconstruction space points is relatively far, marking the corresponding two pixel points in the same cluster of the brightness level of the LED pixel point as similar remote pixel points of the brightness level.

Step S32: combining the pixel points which are adjacent to the pixel points with the same brightness level in the same brightness level cluster as any other pixel point to obtain a similar brightness level adjacent point set; combining the same type of remote pixel points with the same type of brightness level with any other pixel point in the same type of brightness level cluster of the LED pixel points to obtain a same type of remote point set of brightness level;

according to the embodiment of the invention, the relation between each pixel point in the LED pixel point brightness level similar clusters and any other pixel point is checked, if judging that the pixel points are adjacent pixel points with the brightness level similar to any other pixel point, the pixel points are classified into a point set, and the corresponding pixel points are all in the nearby range, so that the brightness level similar adjacent point set is obtained; if the same type of remote pixel points with the brightness level as any other pixel points are judged to be obtained, the same type of remote pixel points with the brightness level are also classified into a point set, and the corresponding pixel points are not in the nearby range or deviate from the corresponding limit area, so that the same type of remote pixel points with the brightness level are finally obtained.

Step S33: resetting the corresponding reconstruction distance standard value to compare and judge the reconstruction distance value between each pixel point in the similar remote point set of the brightness level to obtain another similar adjacent point set of the brightness level and the similar remote point set of the brightness level, and the like until the pixel points in the similar remote point set of the brightness level are zero;

The embodiment of the invention re-compares and judges the reconstruction distance value between each pixel point in the corresponding similar remote point set of the brightness level by resetting the corresponding reconstruction distance standard value (increasing or decreasing), so as to divide the similar remote point set of the brightness level into another adjacent point set and remote point set in a relative remote area through the previous comparison judgment rule, thereby obtaining the similar adjacent point set of the brightness level of the other and the similar remote point set of the brightness level of the other, and the like, and if the pixel points in the similar remote point set of the brightness level are zero, stopping iteration; otherwise, the steps are repeated.

Step S34: carrying out area connection division on each similar adjacent point set of the brightness level to obtain similar pixel connection sub-areas of the brightness level;

According to the embodiment of the invention, the pixel points in the similar adjacent point sets of the brightness level obtained by each classification are subjected to regional connection, so that similar pixel points are aggregated into continuous regions according to the adjacent relation to form larger similar pixel subregions, the relevance and consistency of each part in the pixel space are helped to be identified, and finally the similar pixel connection subregions of the brightness level are obtained.

Step S35: and carrying out chromaticity evaluation analysis on the similar pixel connection subareas of the brightness level to obtain the average chromaticity of the LEDs of the similar pixel subareas.

According to the embodiment of the invention, the color characteristics of each pixel point region in an LED display screen image are accurately described by statistically analyzing the ambient color temperature and the color saturation of each pixel point in each pixel point connecting sub-region, and using a corresponding chromaticity evaluation analysis method to evaluate and analyze each pixel point in each pixel point connecting sub-region, so as to comprehensively consider the ambient color temperature and the color saturation, and determine the chromaticity condition of each pixel point, and meanwhile, the average analysis is carried out on the pixel chromaticity of each pixel point in each pixel connecting sub-region by using an arithmetic average statistical method, so that the average value of the chromaticity values of all pixel points in the corresponding sub-region is calculated statistically, the integral color characteristics of the sub-region are represented, and the average chromaticity of the LEDs of the similar pixel sub-regions is finally obtained.

Firstly, comparing and judging the reconstruction distance value between the reconstruction space points of each similar pixel by using a preset reconstruction distance standard value, and marking the corresponding pixel points in the same-class cluster of the brightness level of the LED pixel as similar adjacent pixel points of the brightness level when the reconstruction distance value between any two similar pixel reconstruction space points is smaller than the preset standard value; otherwise, when the reconstructed distance value is larger than or equal to a preset standard value, marking as the similar remote pixel points of the brightness level, and accurately distinguishing the neighbor relation and the remote relation among the similar pixels through an effective distance standard judging mechanism, so that basic data guarantee is laid for the subsequent area connection processing process. And secondly, merging pixels in the LED pixel brightness level similar clusters, which are adjacent pixels with the same brightness level as any other pixel, and merging pixels in the LED pixel brightness level similar clusters, which are adjacent pixels with the same brightness level as any other pixel, with the same far-reaching pixel, wherein the step aims at merging the pixels with the adjacent relation and the far-reaching relation, so that a larger adjacent point set and a far-reaching point set are formed. And then, comparing and judging the reconstruction distance value between each pixel point in the similar remote point set of the brightness level by resetting the corresponding reconstruction distance standard value, obtaining another similar adjacent point set of the brightness level and the similar remote point set of the brightness level according to the new standard value, and the like until the pixel points in the similar remote point set of the brightness level are zero, wherein the step gradually optimizes and refines the relation between the pixel points through repeated iteration and adjustment, ensures that the data processing of each step can reach the optimal state, and ensures the accuracy and the reliability of the subsequent processing process. Then, by carrying out region connection division on the similar adjacent point sets of the brightness level of each pixel, the main purpose of the step is to aggregate similar pixels into continuous regions according to the adjacent relation to form larger similar pixel sub-regions, and the relevance and consistency of each part in the pixel space can be better identified through region connection division, so that an accurate data basis is provided for subsequent chromaticity evaluation and analysis. Finally, through carrying out chromaticity evaluation analysis on the same pixel connection subareas of the brightness level, the average chromaticity of the subareas can be effectively measured and calculated through carrying out evaluation analysis on the color characteristics of each connection subarea, so that the color distribution and consistency of different areas in the pixel space are further analyzed. Through chromaticity evaluation analysis, scientific basis can be provided for subsequent color processing and optimization, and the best effect of the pixel space on color expression is ensured.

Preferably, step S35 includes the steps of:

Step S351: performing color temperature monitoring analysis on each pixel point in the similar pixel connection sub-area of the brightness level to obtain the ambient color temperature of each pixel point in the similar pixel connection sub-area;

According to the embodiment of the invention, the environment color temperature of each pixel point in the similar pixel connection sub-area of the brightness level is monitored by traversing each pixel point in the similar pixel connection sub-area and performing color temperature monitoring analysis on each pixel point by using a proper color temperature monitoring algorithm, so that the environment color temperature of each pixel point in the similar pixel connection sub-area is finally obtained.

Step S352: carrying out RGB value statistical calculation on each pixel point in the similar pixel connection sub-area of the brightness level to obtain a pixel RGB value of each pixel point in the similar pixel connection sub-area;

according to the embodiment of the invention, the RGB value of the pixel RGB value (specific numerical values including a red channel, a green channel and a blue channel) of the LED display screen at each pixel point is quantitatively calculated by using an RGB value statistical method to perform statistical calculation on each pixel point in the similar pixel connection sub-area of the brightness level, and finally the pixel RGB value at each pixel point in the similar pixel connection sub-area is obtained.

Step S353: carrying out saturation calculation on each pixel point in the similar pixel connection sub-area of the brightness level by utilizing a color saturation calculation formula based on the RGB value of each pixel point in the similar pixel connection sub-area to obtain the color saturation of each pixel point in the similar pixel connection sub-area;

According to the embodiment of the invention, a proper color saturation calculation formula is formed by combining the position variable parameters, the red channel pixel values, the green channel pixel values, the blue channel pixel values, the horizontal gradient influence weight parameters, the vertical gradient influence weight parameters, the space range parameters and the related parameters of the pixel points in the similar pixel connection subarea, so that the saturation of each pixel point in the similar pixel connection subarea of the brightness level is calculated in a quantized manner, the color richness and the vividness of each area in an image are known, and finally the color saturation of each pixel point in the similar pixel connection subarea is obtained.

Step S354: performing chromaticity evaluation analysis on each pixel point in the similar pixel connection sub-area of the brightness level according to the ambient color temperature and the color saturation of each pixel point in the similar pixel connection sub-area to obtain the pixel chromaticity of each pixel point in the similar pixel connection sub-area;

According to the embodiment of the invention, the environmental color temperature and the color saturation of each pixel point in the similar pixel connection sub-area obtained through combination analysis are evaluated and analyzed by using a corresponding chromaticity evaluation analysis method, so that the color characteristics of each pixel point area in the LED display screen image are accurately described by comprehensively considering the environmental color temperature and the color saturation, the chromaticity condition of each pixel point is determined, the color characteristics and the color accuracy are reflected, and the pixel chromaticity of each pixel point in the similar pixel connection sub-area is finally obtained.

Step S355: and carrying out arithmetic average analysis on the pixel chromaticity of each pixel point in the similar pixel connection sub-area to obtain the average chromaticity of the LEDs in the similar pixel sub-area.

According to the embodiment of the invention, the average analysis is carried out on the pixel chromaticity of each pixel point in the similar pixel connection subarea by using an arithmetic average statistical method, so that the average value of the chromaticity values of all the pixel points in the corresponding subarea is calculated in a statistical manner, the integral color characteristic of the subarea is represented, and the average chromaticity of the LEDs of the similar pixel subareas is finally obtained.

According to the invention, the color temperature monitoring analysis is carried out on each pixel point in the similar pixel connection subarea of the brightness level, so that the ambient color temperature at each pixel point can be obtained, the ambient color temperature refers to the tone of light emitted by an object, the size of the ambient color temperature is related to the color of a light source, and the cold and warm degree of the light source is reflected. By monitoring and analyzing the ambient color temperature of the pixel points, the light source conditions of different areas in the image can be known, and important references are provided for subsequent color evaluation and adjustment. And secondly, carrying out RGB value statistics calculation on each pixel point in the pixel connection sub-area of the same brightness level to obtain a pixel RGB value at each pixel point, wherein the RGB value is a numerical representation of three primary colors of red, green and blue, the color distribution condition of the pixel point in an image can be reflected, and the step can be used for deeply knowing the color composition of different areas in the image by carrying out statistics calculation on the RGB value of the pixel, so that basic data is provided for subsequent color analysis and processing. Then, the color saturation is obtained by calculating the saturation of each pixel point based on the RGB value of the pixel at each pixel point and by using a proper color saturation calculation formula, the color shade degree of the color can be reflected, and the color richness and the vividness of each region in the image can be known by calculating the color saturation of each pixel point, so that important data support is provided for subsequent color evaluation and adjustment. Then, by performing chromaticity evaluation analysis on each pixel according to the ambient color temperature and the color saturation at each pixel, the chromaticity refers to the hue or hue of the color, and the basic attribute of the color is reflected. Finally, the average chromaticity of the whole area can be obtained by carrying out arithmetic average analysis on the chromaticity of the pixels at each pixel point in the similar pixel connection sub-area, and the integral color characteristics of the area are further reflected, so that visual reference basis is provided for subsequent color adjustment and optimization, and the uniformity and accuracy of the color representation of the image pixel space are ensured.

Preferably, the color saturation calculation formula in step S353 is specifically:

Where S (x, y) is the color saturation of the pixel point in the similar pixel connection sub-area at the position (x, y), x is the horizontal position parameter of the pixel point in the similar pixel connection sub-area, y is the vertical position parameter of the pixel point in the similar pixel connection sub-area, R (x, y) is the red channel pixel value of the pixel point in the similar pixel connection sub-area at the position (x, y), G (x, y) is the green channel pixel value of the pixel point in the similar pixel connection sub-area at the position (x, y), B (x, y) is the blue channel pixel value of the pixel point in the similar pixel connection sub-area at the position (x, y), ρ ₁ is the horizontal gradient influence weight parameter, ρ ₂ is the vertical gradient influence weight parameter, Ω is the spatial range parameter of the luminance horizontal similar pixel connection sub-area, and ζ is the correction coefficient of the color saturation.

The invention obtains a color saturation calculation formula by using a specific mathematical model and verifying, and is used for calculating the saturation of each pixel point in the pixel connection subarea of the same brightness level, the RGB value in the color saturation calculation formula reflects the brightness of the pixel point on three channels of red, green and blue, and the synthesis can help to capture the color information of the pixel point instead of the brightness of a single channel. The formula also contains consideration of gradients, and the change condition of the color around the pixel point can be reflected through calculation of horizontal and vertical gradients, so that the calculation of the color saturation can be more detailed and accurate through the consideration. Second, Ω in the formula represents the spatial extent of the pixel connection sub-areas of the same class of luminance levels, which allows the calculation to take into account the spatial distribution of the pixel points. By considering the space range, the correlation between the pixel points can be better captured, so that the calculation accuracy of the color saturation is improved. In addition, the formula also introduces a correction coefficient of color saturation, and the correction coefficient can be used for adjusting a calculation result so as to adapt to different application scenes or improve the accuracy of calculation. Through the comprehensive consideration, the color saturation of each pixel point in the similar pixel connection subarea can be well estimated, so that important data support is provided for subsequent chromaticity estimation and analysis. Therefore, the formula can fully consider the color saturation S (x, y) of the pixel point in the similar pixel connection sub-area at the position (x, y), the horizontal position parameter x of the pixel point in the similar pixel connection sub-area, the vertical position parameter y of the pixel point in the similar pixel connection sub-area, the red channel pixel value R (x, y) of the pixel point in the similar pixel connection sub-area at the position (x, y), the green channel pixel value G (x, y) of the pixel point in the similar pixel connection sub-area at the position (x, y), the blue channel pixel value B (x, y) of the pixel point in the similar pixel connection sub-area at the position (x, y), the horizontal gradient influence weight parameter ρ ₁, the vertical gradient influence weight parameter ρ ₂, the spatial range parameter Ω of the luminance horizontal similar pixel connection sub-area, the correction coefficient ζ of the color saturation, and a function relationship formed according to the color saturation S (x, y) of the pixel point in the similar pixel connection sub-area at the position (x, y) and the above parameters.

The formula can realize the saturation calculation process of each pixel point in the pixel connection subarea of the same brightness level, and can be adjusted according to the error condition in the calculation process by introducing the correction coefficient xi of the color saturation, thereby improving the accuracy and the applicability of the color saturation calculation formula.

Preferably, step S4 comprises the steps of:

step S41: performing brightness difference evaluation analysis on the same-kind pixel connection subareas with different brightness levels to obtain brightness difference factors among the same-kind pixel connection subareas;

According to the embodiment of the invention, the pixel connection subareas with the same brightness level are divided into a plurality of groups of pixel subareas with different categories according to different categories, each group comprises the pixel connection subareas with similar brightness level characteristics, the brightness levels among the pixel connection subareas with the same brightness level in different categories are subjected to difference evaluation analysis by using a proper brightness difference evaluation method (such as a mean square error method, a brightness histogram difference method and the like) so as to compare the brightness levels of the pixel connection subareas with the different categories to determine the brightness performance of different areas of the LED display screen, and the brightness difference factors among the pixel connection subareas with different groups are evaluated and calculated, so that the problem of the brightness non-uniformity is found, and finally the brightness difference factors among the pixel connection subareas with different categories are obtained.

Step S42: performing chromaticity difference evaluation analysis on the same-class pixel connection subareas with different classes of brightness levels based on the average chromaticity of the LEDs in the same-class pixel subareas to obtain chromaticity difference factors among the different same-class pixel connection subareas;

According to the embodiment of the invention, the average chromaticity of the LEDs in the similar pixel subregions obtained through combination analysis is subjected to difference evaluation analysis on the chromaticity levels between the similar pixel connection subregions of different types of brightness levels by using a proper chromaticity difference evaluation method (such as a chromaticity histogram comparison method, a chromaticity distance calculation method and the like) so as to analyze and reflect the color expression difference degree of different areas of an LED display screen, evaluate and calculate chromaticity difference factors between the different pixel connection subregions, find areas with inconsistent colors or larger deviation, and finally obtain the chromaticity difference factors between the different similar pixel connection subregions.

Step S43: carrying out luminance and chrominance deviation statistical analysis on the same-type pixel connection subareas of the luminance level based on the luminance difference factors and the chrominance difference factors among different same-type pixel connection subareas to obtain luminance and chrominance deviation degree coefficients of the same-type pixel connection subareas;

According to the embodiment of the invention, the luminance difference factors and the chromaticity difference factors among different similar pixel connection subareas obtained through combination analysis are used for carrying out luminance and chromaticity difference statistical analysis on the corresponding luminance level similar pixel connection subareas by using a difference statistical analysis method (such as a mean value, a standard deviation and a correlation coefficient) so as to comprehensively consider the luminance and chromaticity difference to quantify the luminance and chromaticity difference degree coefficient of each area and help to determine which areas need to be adjusted to achieve more uniform luminance and color expression, and finally the luminance and chromaticity difference degree coefficient of the similar pixel connection subareas is obtained.

Step S44: and carrying out current driving correction analysis on the similar pixel connection subareas of the brightness level according to the brightness deviation degree coefficients of the similar pixel connection subareas so as to obtain the LED display brightness deviation correction result.

According to the embodiment of the invention, the luminance deviation degree threshold value is used for comparing and judging the luminance deviation degree coefficient of the similar pixel connection subarea obtained through statistical calculation, if the luminance deviation degree coefficient of the similar pixel connection subarea is smaller than the preset luminance deviation degree threshold value, the fact that the luminance deviation does not exist in the pixel subarea corresponding to the luminance deviation degree coefficient is indicated, no processing is carried out, and if the luminance deviation degree coefficient of the similar pixel connection subarea is larger than or equal to the preset luminance deviation degree threshold value, the fact that the pixel subarea corresponding to the luminance deviation degree coefficient has large luminance deviation is indicated, corresponding current driving correction is carried out on the luminance deviation subarea, so that current driving parameters of LEDs in the corresponding area are adjusted, for example, current driving of LED lamps in an LED display screen is increased or decreased, the deviation between the luminance and the chromaticity of the LEDs is reduced, the display effect of the corrected LED display screen subarea is more uniform and consistent, and finally the luminance deviation correction result of the LED display is obtained.

According to the invention, firstly, the brightness difference evaluation analysis is carried out on the similar pixel connection subareas with different brightness levels, which is helpful for identifying and quantifying the brightness difference factors among different areas, and the step can determine the brightness performance of different areas of the LED display screen by comparing the brightness levels of the pixel connection subareas with different categories, thereby helping to find the problem of uneven brightness, and providing an important basis for subsequent adjustment. And secondly, carrying out chromaticity difference evaluation analysis on the similar pixel connection subareas with different types of brightness levels based on the average chromaticity of the similar pixel subareas, so that chromaticity difference factors among different areas can be obtained, the chromaticity difference factors reflect the color expression difference degrees of the different areas of the LED display screen, the areas with inconsistent colors or larger deviation can be found, and guidance is provided for subsequent color correction. Then, by performing luminance deviation statistical analysis on the luminance level homogeneous pixel connection subregions based on the luminance difference factors and the chrominance difference factors between the different homogeneous pixel connection subregions, the purpose of this step is to comprehensively consider the luminance and chrominance differences to quantify the luminance deviation degree coefficients of the respective regions, which coefficients can help determine which regions need to be adjusted to achieve more uniform luminance and color representation. Finally, current driving correction analysis is carried out on the similar pixel connection subareas with the brightness level according to the similar pixel connection subarea brightness deviation degree coefficient, and a corresponding current driving correction strategy is formulated according to the corresponding brightness deviation coefficient, wherein the current driving of the LED lamps in the LED display screen is increased or reduced, so that the brightness of different areas of the LED display screen can be adjusted to be more uniform, the overall visual effect of the LED display screen is improved, and the LED display screen can be ensured to display accurate, bright colors and bright pictures.

The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. The brightness and color correction method for the LED display screen is characterized by comprising the following steps of:

Step S2: performing pixel space optimization conversion on each pixel point in the LED pixel point brightness level similar clusters to obtain a brightness level similar pixel reconstruction space point set; performing reconstruction distance calculation on the similar pixel reconstruction space point set of the brightness level to obtain a reconstruction distance value between the similar pixel reconstruction space points; wherein, step S2 includes the following steps:

step S25: performing reconstruction distance calculation on the pixel reconstruction space point set of the same type of brightness level by using a pixel reconstruction distance calculation formula to obtain a reconstruction distance value between the reconstruction space points of each same type of pixel; the pixel reconstruction distance calculation formula specifically comprises:

Wherein D (p, q) is a reconstruction distance value between a p-th similar pixel reconstruction space point and a q-th similar pixel reconstruction space point, p, q are each a term index parameter of a similar pixel reconstruction space point in a brightness level similar pixel reconstruction space point set, I _p is a brightness value at the p-th similar pixel reconstruction space point, I _q is a brightness value at the q-th similar pixel reconstruction space point, alpha is a brightness weight coefficient, Pixel gradient values at spatial points are reconstructed for the p-th homogeneous pixel,For a pixel gradient value at a q-th similar pixel reconstruction space point, β is a pixel gradient weight coefficient, T _p is a pixel texture feature value at a p-th similar pixel reconstruction space point, T _q is a pixel texture feature value at the q-th similar pixel reconstruction space point, γ is a pixel texture feature weight coefficient, B _p is a pixel edge feature value at the p-th similar pixel reconstruction space point, B _q is a pixel edge feature value at the q-th similar pixel reconstruction space point, δ is a pixel edge feature weight coefficient, and η is a correction coefficient of a reconstruction distance value;

2. The method of correcting brightness and color of an LED display screen according to claim 1, wherein the step S1 comprises the steps of:

3. The method of correcting brightness and color of an LED display screen according to claim 1, wherein the step S24 comprises the steps of:

4. The method of correcting brightness and color of an LED display screen according to claim 1, wherein the step S3 comprises the steps of:

5. The method of calibrating brightness and color of an LED display screen according to claim 4, wherein step S35 comprises the steps of:

6. The method according to claim 5, wherein the color saturation calculation formula in step S353 is specifically:

7. The method of correcting brightness and color of an LED display screen according to claim 1, wherein the step S4 comprises the steps of:

8. An LED display screen brightness correction system for performing the LED display screen brightness correction method of claim 1, the LED display screen brightness correction system comprising: