Objective quantitative evaluation method and device for Demura effect

Abstract

The invention discloses an objective quantitative evaluation method and device for a Demura effect. The method comprises the following steps: firstly, respectively calculating corresponding gray scale brightness under target brightness, an observation angle corresponding to an observation screen and spatial frequencies corresponding to SandyMura of different sizes; secondly, contrast thresholds corresponding to different sizes of SandyMura are calculated by using the parameters and a Barten model; then determining the combination proportion of each monochromatic data according to the mean value of the monochromatic shooting data center area; combining the monochromatic shooting data into white shooting data by using the combination proportion; the contrast ratio of SandyMura of different sizes in the white shooting data is calculated, and SandyMura scoring is carried out on each point; and finally, calculating a full-screen Sandy Mura evaluation result.

Description

Technical Field

[0001] The invention belongs to the field of image processing and relates to an objective quantitative evaluation method and device for Demura effect. Background Art

[0002] An AMOLED screen (full name: Active Matrix Organic Light Emitting Diode) is a screen structure that does not require a backlight and uses an organic material layer and a glass substrate. Its self-luminous properties offer considerable advantages in terms of screen power consumption, brightness, and contrast. In each step of the panel manufacturing process, film formation, crystallization, uneven etching, and differences in alignment can all cause uneven brightness and color on the display panel, a phenomenon known as mura. Sandy mura (gritty mura) is a defect that occurs during the production process. It manifests itself as pixel electrodes breaking due to excessive etching, which in turn causes abnormal deflection of liquid crystal molecules, forming dark spots. Mura can be eliminated in three main ways: process improvement, internal compensation, and external compensation. External compensation involves adding a demura compensation circuit to compensate for the brightness and color of the screen.

[0003] The effectiveness of demura compensation circuits relies on visual assessment by experienced quality control personnel, which can lead to subjective differences in evaluation results. To mitigate these differences, a method is needed that can capture data directly through optical instruments and perform algorithmic analysis and assessment of demura effects without relying on quality control personnel. Furthermore, the results of this method must be as consistent as possible with human visual observation and assessment.

[0004] To this end, the present invention proposes a method and device for objectively and quantitatively evaluating the demura effect. Summary of the Invention

[0005] The present invention provides an objective quantitative evaluation method for demura effect, comprising: Step 1: Calculate the corresponding grayscale brightness at the target brightness, the corresponding viewing angle of the observation screen, and the corresponding spatial frequency of SandyMura of different sizes; Step 2: Use the parameters in step 1 and the Barten 1990 model to calculate the contrast thresholds corresponding to SandyMura of different sizes; Step 3: Determine the combination ratio of each monochrome data according to the average value of the center area of ​​the monochrome shooting data; Step 4: Combine the monochrome shooting data into white shooting data using the combination ratio in step 3; Step 5: Calculate the contrast of SandyMura of different sizes in the white shooting data and perform SandyMura scoring for each point Step 6. Calculate the full-screen SandyMura score.

[0006] In step 1, assuming that the grayscale corresponding to the current shooting data is gray, the corresponding brightness L of the current grayscale is calculated using the following formula: ,in, is the target brightness of 255 grayscale, ; In order to obtain the observation angle of the AMOLED screen in human vision , calculated as , where S is the horizontal width of the screen in cm, D is the distance from the human eye to the screen in cm, assuming that the space occupied by Sandy Mura is When the Mura is dense enough, it looks like a checkerboard pattern. The spatial frequencies corresponding to Sandy Mura of different sizes are calculated: , where W is the number of horizontal pixels on the screen, For the observation angle.

[0007] In step 2, the contrast sensitivity function of the Barten 1990 model is calculated as follows , where a, b, and c are adjustment parameters. , , , is the viewing angle, L is the corresponding brightness of the current grayscale, and the contrast threshold is the reciprocal of contrast sensitivity, calculated separately Corresponding spatial frequency , and the contrast threshold .

[0008] In step 3, the color analyzer is used to measure the absolute brightness ratio of the central area of ​​each monochrome image at the corresponding grayscale, and the ratio is used to correct the monochrome shooting data. Assume that the monochrome shooting data of the i-th row and j-th column is , and take the central area to calculate the average value , assuming that the brightness of the RGB image measured by the color analyzer is , then use the following coefficients Correction of monochrome shooting data .

[0009] The calculation formula in step 4 is: .

[0010] In step 5, the white shooting data is The mean filter is used to calculate the background brightness of the area. M is an odd number. , where m is a natural number, ; The white shooting data are The mean filter calculates the average brightness of different block sizes. If N is an odd number, , where n is a natural number, , if N is an even number, , ,in .

[0011] The contrast of SandyMura at different sizes is expressed as , , the SandyMura score of each point is calculated as follows: ,in, Indicates taking the maximum value, The maximum value of the ratio of the contrast of each point to the contrast threshold at different sizes, Each point is scored with a SandyMura score ranging from 0 to 100.

[0012] In step 6, it is assumed that the scoring threshold that can be set is , and the number of screen pixel rows is H, the number of pixel columns is W, and each pixel is binarized using the scoring threshold , then the full-screen SandyMura score is expressed as ,in, , The range is 0~100.

[0013] The present invention also provides an objective quantitative evaluation device for demura effect, comprising: The shooting data preprocessing module calculates the input monochrome brightness shooting data according to a specific ratio to obtain the brightness shooting data of the white screen and transmits it to the filtering and contrast calculation module; The filtering and contrast calculation module performs different degrees of filtering on the brightness data of the white screen and calculates the contrast of different levels of Sandy Mura; The contrast threshold calculation module uses the input prediction model parameters to calculate the contrast threshold of Sandy Mura of different sizes; The single-point Sandy Mura degree assessment module combines the contrast ratio of different sandy mura sizes and the contrast threshold ratio to perform single-point Sandy Mura degree assessment and transmits the single-point assessment result to the full-screen Sandy Mura degree assessment module. The full-screen Sandy Mura level determination module combines the single-point Sandy Mura performance to calculate the full-screen Sandy Mura level determination result.

[0014] Based on experimental observations and data fitting, this model generates an observation curve that closely matches the characteristics of the human eye, fully accounting for the impact of factors such as brightness, viewing distance and angle, and spatial frequency on human visual characteristics. The objective quantitative evaluation method for demura effects proposed in this paper can effectively replace the scientific demura effect assessment performed by quality control personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Shown is a flow chart of the present invention; Figure 2 Shown is a schematic diagram of the screen observation viewing angle of the present invention; Figure 3 Shown are checkerboards of different sizes according to the present invention; Figure 4 Shown are the CSF function and Mt function curves of the present invention; Figure 5 Shown is a schematic diagram of the device of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See Figure 1-5 The present invention provides an objective quantitative evaluation method for Demura effect, comprising: Step 1: Calculate the corresponding grayscale brightness at the target brightness, the corresponding viewing angle of the observation screen, and the corresponding spatial frequency of SandyMura of different sizes; Step 2: Use the parameters in step 1 and the Barten 1990 model to calculate the contrast thresholds corresponding to SandyMura of different sizes; Step 3: Determine the combination ratio of each monochrome data according to the average value of the center area of ​​the monochrome shooting data; Step 4: Combine the monochrome shooting data into white shooting data using the combination ratio in step 3; Step 5: Calculate the contrast of SandyMura of different sizes in the white shooting data and perform SandyMura scoring for each point Step 6. Calculate the full-screen SandyMura score.

[0018] In step 1, assuming that the grayscale corresponding to the current shooting data is gray, the corresponding brightness L of the current grayscale is calculated using the following formula: ,in, is the target brightness of 255 grayscale, ; In order to obtain the observation angle of the AMOLED screen in human vision , calculated as , where S is the horizontal width of the screen in cm, D is the distance from the human eye to the screen in cm, assuming that the space occupied by Sandy Mura is When the Mura is dense enough, it looks like a checkerboard pattern. The spatial frequencies corresponding to Sandy Mura of different sizes are calculated: , where W is the number of horizontal pixels on the screen, For the observation angle.

[0019] In step 2, the contrast sensitivity function of the Barten 1990 model is calculated as follows ,in, , , , is the viewing angle, L is the corresponding brightness of the current grayscale, and the contrast threshold is the reciprocal of contrast sensitivity, calculated separately Corresponding spatial frequency , and the contrast threshold .

[0020] In step 3, since the monochrome shooting data is a relative brightness value, it cannot be directly added together to form the white shooting data. If you want to obtain the brightness distribution under the white screen, you need to first use a color analyzer to measure the absolute brightness ratio of the central area of ​​each monochrome screen corresponding to the grayscale, and use this ratio to correct the monochrome shooting data. Assume that the monochrome shooting data of the i-th row and j-th column is , and take the central area to calculate the average value , assuming that the brightness of the RGB image measured by the color analyzer is , then use the following coefficients Correction of monochrome shooting data .

[0021] The calculation formula in step 4 is: .

[0022] In step 5, the white shooting data is The mean filter is used to calculate the background brightness of the area. M is an odd number. , ; Where M is usually large, such as M=31; The white shooting data are The mean filter calculates the average brightness of different block sizes. If N is an odd number, , , if N is an even number, , ,in .

[0023] The contrast of SandyMura at different sizes is expressed as , , the SandyMura score of each point is calculated as follows: ,in, Indicates taking the maximum value, The maximum value of the ratio of the contrast of each point to the contrast threshold at different sizes, Each point is scored with a SandyMura score ranging from 0 to 100.

[0024] In step 6, it is assumed that the scoring threshold that can be set is , and the number of screen pixel rows is H, the number of pixel columns is W, and each pixel is binarized using the scoring threshold , then the full-screen SandyMura score is expressed as ,in, , The range is 0~100.

[0025] The present invention also provides an objective quantitative evaluation device for demura effect, comprising: The shooting data preprocessing module calculates the input monochrome brightness shooting data according to a specific ratio to obtain the brightness shooting data of the white screen and transmits it to the filtering and contrast calculation module; The filtering and contrast calculation module performs different degrees of filtering on the brightness data of the white screen and calculates the contrast of different levels of Sandy Mura; The contrast threshold calculation module uses the input prediction model parameters to calculate the contrast threshold of Sandy Mura of different sizes; The single-point Sandy Mura degree assessment module combines the contrast ratio of different sandy mura sizes and the contrast threshold ratio to perform single-point Sandy Mura degree assessment and transmits the single-point assessment result to the full-screen Sandy Mura degree assessment module. The full-screen Sandy Mura level determination module combines the single-point Sandy Mura performance to calculate the full-screen Sandy Mura level determination result.

[0026] The proposed method primarily assesses Sandy Mura. The assessment of other types of mura, such as brightness and color uniformity, is relatively simple. This method can be combined with other methods for assessing these types of mura to achieve a more comprehensive, integrated evaluation. Furthermore, in assessing Sandy Mura, differentiated thresholds are applied based on the size of the mura, ensuring a more consistent automated assessment with human judgment and a more objective and accurate evaluation result.

[0027] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is limited by the appended claims and their equivalents.

Claims

1. An objective quantitative evaluation method for Demura effect, characterized in that include: Step 1: Calculate the corresponding grayscale brightness at the target brightness, the corresponding viewing angle of the observation screen, and the corresponding spatial frequency of SandyMura of different sizes; Step 2: Use the parameters in step 1 and the Barten 1990 model to calculate the contrast thresholds corresponding to SandyMura of different sizes; Step 3: Determine the combination ratio of each monochrome data according to the average value of the center area of ​​the monochrome shooting data; Step 4: Combine the monochrome shooting data into white shooting data using the combination ratio in step 3; Step 5: Calculate the contrast of SandyMura of different sizes in the white shooting data and perform SandyMura scoring for each point Step 6. Calculate the full-screen SandyMura score.

2. The objective quantitative evaluation method for demura effect according to claim 1, characterized in that: In step 1, assuming that the grayscale corresponding to the current shooting data is gray, the corresponding brightness L of the current grayscale is calculated using the following formula: ,in, is the target brightness of 255 grayscale, ; In order to obtain the observation angle of the AMOLED screen in human vision , calculated as , where S is the horizontal width of the screen in cm, D is the distance from the human eye to the screen in cm, assuming that the space occupied by Sandy Mura is When the Mura is dense enough, it looks like a checkerboard pattern. The spatial frequencies corresponding to Sandy Mura of different sizes are calculated: , where W is the number of horizontal pixels on the screen, For the observation angle.

3. The objective quantitative evaluation method of demura effect according to claim 2, characterized in that: In step 2, the contrast sensitivity function of the Barten 1990 model is calculated as follows , where a, b, and c are adjustment parameters. , , , is the viewing angle, L is the corresponding brightness of the current grayscale, and the contrast threshold is the reciprocal of contrast sensitivity, calculated separately Corresponding spatial frequency , and the contrast threshold .

4. The objective quantitative evaluation method of demura effect according to claim 3, characterized in that: In step 3, the color analyzer is used to measure the absolute brightness ratio of the central area of ​​each monochrome image at the corresponding grayscale, and the ratio is used to correct the monochrome shooting data. Assume that the monochrome shooting data of the i-th row and j-th column is , and take the central area to calculate the average value , assuming that the brightness of the RGB image measured by the color analyzer is , then use the following coefficients Correction of monochrome shooting data .

5. The objective quantitative evaluation method of demura effect according to claim 4, characterized in that: The calculation formula in step 4 is: 。 6. The objective quantitative evaluation method of demura effect according to claim 5, characterized in that: In step 5, the white shooting data is The mean filter is used to calculate the background brightness of the area. M is an odd number. , ; where m is a natural number, The white shooting data are The mean filter calculates the average brightness of different block sizes. If N is an odd number, , where n is a natural number, , if N is an even number, , ,in .

7. The objective quantitative evaluation method of demura effect according to claim 6, characterized in that: The contrast of SandyMura at different sizes is expressed as , , the SandyMura score of each point is calculated as follows: ,in, Indicates taking the maximum value, The maximum value of the ratio of the contrast of each point to the contrast threshold at different sizes, Each point is scored with a SandyMura score ranging from 0 to 100.

8. The objective quantitative evaluation method of demura effect according to claim 7, characterized in that: In step 6, it is assumed that the scoring threshold that can be set is , and the number of screen pixel rows is H, the number of pixel columns is W, and each pixel is binarized using the scoring threshold , then the full-screen SandyMura score is expressed as ,in, , The range is 0~100.

9. An objective quantitative evaluation device for demura effect, using any objective quantitative evaluation method for demura effect according to any one of claims 1 to 8, characterized in that: include: The shooting data preprocessing module calculates the input monochrome brightness shooting data according to a specific ratio to obtain the brightness shooting data of the white screen and transmits it to the filtering and contrast calculation module; The filtering and contrast calculation module performs different degrees of filtering on the brightness data of the white screen and calculates the contrast of different levels of Sandy Mura; The contrast threshold calculation module uses the input prediction model parameters to calculate the contrast threshold of Sandy Mura of different sizes; The single-point Sandy Mura degree assessment module combines the contrast ratio of different sandy mura sizes and the contrast threshold ratio to perform single-point Sandy Mura degree assessment and transmits the single-point assessment result to the full-screen Sandy Mura degree assessment module. The full-screen Sandy Mura level determination module combines the single-point Sandy Mura performance to calculate the full-screen Sandy Mura level determination result.

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