High-precision quantitative testing method and device for ghosting of display module

Abstract

The invention discloses a high-precision quantitative test method and device for display module ghosting, and the method comprises the steps: constructing a ghosting grade quantitative judgment model, and driving a to-be-tested display module to display a composite test image; calculating to obtain a brightness difference according to the first brightness data, calculating to obtain a brightness decay rate according to the second brightness data, calculating to obtain a frequency domain energy ratio according to the brightness image data, and calculating to obtain a chromaticity deviation according to an actual color value parameter; and according to the brightness decay rate, the brightness difference, the frequency domain energy ratio and the chromaticity deviation which are obtained through calculation, the ghosting level of the display module is quantized by using a ghosting level quantization judgment model. The ghosting detection judgment precision is improved, and the problem that an existing ghosting detection method is prone to being influenced by factors such as environment influence and one-sided detection, and consequently the detection result is inaccurate is solved.

Description

Technical Field

[0001] This invention relates to the field of image retention testing technology, and in particular to a high-precision quantitative testing method and apparatus for image retention of display modules. Background Technology

[0002] In the field of display modules, image retention is an important indicator for measuring the optical parameters of display modules. It refers to the phenomenon where, when a display screen shows an image for an extended period, charged particles in the liquid crystal adhere to the upper and lower glass surfaces, creating a built-in electric field. After the image changes, these charged particles are not immediately released, causing the liquid crystal molecules to not immediately rotate to the corresponding angle, resulting in image retention. Additionally, poor design during the pixel electrode design phase can also cause misalignment of liquid crystal molecules during image transitions, leading to image retention.

[0003] Image retention can negatively impact a user's viewing experience. When a user views one image on the screen, and that image doesn't disappear promptly, it overlaps with the next image, significantly reducing the user experience. Existing image retention testing methods sometimes rely on the subjective judgment of operators, who are easily influenced by sensory perception and the testing environment, leading to errors in judgment during production testing. Other methods utilize detection devices, but these devices rely solely on brightness parameters or frequency domain characteristics, failing to comprehensively consider multi-dimensional influencing factors such as brightness attenuation and color deviation, resulting in insufficient accuracy. Furthermore, some methods have complex testing procedures and excessively long testing times, making them unsuitable for the efficient testing needs of mass production lines. Summary of the Invention

[0004] Existing methods for detecting image retention are susceptible to environmental influences and limitations in detection methods, which can lead to inaccurate results.

[0005] To address the aforementioned issues, a high-precision quantitative testing method and device for display module ghosting is proposed. By constructing a ghosting level quantification judgment model, the display module under test is driven to display a composite test image. First brightness data of the black and white grid area, second brightness data of the multi-level intermediate grayscale area, time-domain data of the brightness image, and actual color value parameters of the color area are collected. Based on the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio, and chromaticity deviation, the ghosting level of the display module is quantified using the ghosting level quantification judgment model. This improves the accuracy of ghosting judgment and solves the problems of existing ghosting detection methods being susceptible to environmental influences and biased detection, leading to inaccurate test results.

[0006] Firstly, a high-precision quantitative testing method for display module afterimages includes: Step 100: Construct a quantification model for afterimage level and drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least red blocks, green blocks, blue blocks, and white and yellow mixed color blocks. Step 200: Collect the time-domain data of the brightness image of the composite test screen, including the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area. Calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the brightness image data, and calculate the color deviation based on the actual color value parameters. Step 300: Obtain the image retention level quantization judgment model, and quantify the image retention level of the display module based on the calculated brightness attenuation rate, brightness difference, frequency domain energy ratio and chromaticity deviation using the image retention level quantization judgment model.

[0007] In conjunction with the high-precision quantification test method for display module afterimages described in the first aspect of the present invention, in a first possible embodiment, before step 100, the method includes: Step 101: Set up a test environment that is compatible with the model of the display module and calibrate the brightness of the display module using the brightness standard reference value; Step 102: After the test environment is set up, drive the display module to display the preset stress duration.

[0008] In conjunction with the high-precision quantification test method for display module afterimages described in the first aspect of the present invention, in a second possible embodiment, step 100 includes: Step 110: Classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into different levels; Step 120: Construct the afterimage level quantization judgment model by using the brightness attenuation rate range, brightness difference range, chromaticity difference range and frequency domain energy ratio range after the level division.

[0009] In conjunction with the second possible implementation of the first aspect of the present invention, in the third possible implementation, step 200 includes: Step 210: Obtain the real-time brightness value and brightness standard reference value of the multi-level intermediate grayscale region, and obtain the stable brightness value of the multi-level intermediate grayscale region displayed for a specified time. Step 220: Calculate the brightness attenuation rate based on the brightness standard reference value, the real-time brightness value, and the stable brightness value.

[0010] In conjunction with the second possible implementation of the first aspect of the present invention, in the fourth possible implementation, step 200 includes: Step 230: Collect the brightness values ​​of the black squares and the white squares in the black and white square area at the same time. Step 240: Calculate the brightness difference based on the brightness values ​​of the black squares and the brightness values ​​of the white squares.

[0011] In conjunction with the second possible implementation of the first aspect of the present invention, in the fifth possible implementation, step 200 includes: Step 250: Acquire the luminance component, red-green component, and yellow-blue component in the color region; Step 260: Calculate the differences between the luminance component, red-green component, and yellow-blue component and the reference chromaticity, respectively. Step 270: Calculate the chromaticity deviation based on the luminance component difference, red-green component difference, and yellow-blue component difference.

[0012] In conjunction with the second possible implementation of the first aspect of the present invention, in the sixth possible implementation, step 200 includes: Step 280: Obtain the time domain data of the brightness image, and perform Fourier transform on the brightness image data to obtain the frequency domain data of the brightness image; Step 290: Extract the first spectral energy value corresponding to the spatial frequency of the afterimage feature in the brightness image frequency domain data, and obtain the second spectral energy value of the uniform reference grayscale image spectrum; Step 291: Calculate the frequency domain energy ratio based on the first spectral energy value and the second spectral energy value.

[0013] Secondly, a high-precision quantization testing device for display module afterimages, employing the high-precision quantization testing method for display module afterimages described in the first aspect, includes: The module is used to construct a quantitative judgment model for the level of afterimage using the range of brightness attenuation rate, brightness difference range, chromaticity difference range, and frequency domain energy ratio range. The driving module is used to drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least a red block, a green block, a blue block, and a white and yellow mixed color block. The acquisition module is used to acquire the time-domain data of the brightness image of the composite test screen, the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area; The calculation module is used to calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the time domain data of the brightness image, and calculate the color deviation based on the actual color value parameters. The quantization judgment module is used to obtain the afterimage level quantization judgment model, and quantify the afterimage level of the display module according to the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio and chromaticity deviation, and the afterimage level quantization judgment model.

[0014] In conjunction with the high-precision quantization testing device for display module afterimages described in the second aspect of the present invention, in a first possible embodiment, the building module includes: The division unit is used to classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into levels; The construction unit is used to construct the afterimage level quantization judgment model by utilizing the brightness attenuation rate range, brightness difference range, chromaticity difference range and frequency domain energy ratio range after the level division.

[0015] In conjunction with the high-precision quantization testing device for display module afterimages described in the second aspect of the present invention, in a second possible embodiment, the calculation module includes: The first calculation unit is used to calculate the brightness attenuation rate based on the brightness standard reference value, the real-time brightness value and the stable brightness value. The second calculation unit is used to calculate the brightness difference based on the brightness values ​​of the black squares and the brightness values ​​of the white squares. The third calculation unit is used to calculate the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity differences from the corresponding reference chromaticity, and to calculate the chromaticity deviation based on the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity. The fourth calculation unit is used to calculate the frequency domain energy ratio based on the first spectral energy value and the second spectral energy value.

[0016] The high-precision quantitative testing method and apparatus for display module afterimages described in this invention constructs an afterimage level quantification judgment model, drives the display module under test to display a composite test screen, collects the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area and the time domain data of the brightness image, and the actual color value parameters of the color area. Based on the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio and chromaticity deviation, and using the afterimage level quantification judgment model, the afterimage level of the display module is quantified, which improves the accuracy of afterimage judgment and solves the problem that existing afterimage detection methods are easily affected by environmental factors and detection bias, which leads to inaccurate detection results. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of a specific embodiment of a high-precision quantitative testing method for display module afterimages in this invention. Figure 2 for Figure 1 A schematic diagram of a specific implementation prior to step 100; Figure 3 for Figure 1 A schematic diagram of a specific implementation of step 100 in the diagram; Figure 4 for Figure 1 A schematic diagram of a specific implementation of step 200 in the diagram; Figure 5 for Figure 4 A schematic diagram of a specific implementation method following step 220; Figure 6 for Figure 5 A schematic diagram of a specific implementation method following step 240; Figure 7 for Figure 6 A schematic diagram of a specific implementation method following step 270; Figure 8 This is a schematic diagram illustrating a specific implementation of a high-precision quantitative testing device for display module afterimages according to the present invention. Detailed Implementation

[0019] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are all within the scope of protection of this invention.

[0020] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings of this application are intended to cover non-exclusive inclusion.

[0022] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0023] Existing methods for detecting image retention are susceptible to environmental influences and limitations in detection methods, which can lead to inaccurate results.

[0024] To address the above problems, a high-precision quantitative testing method and device for display module afterimages are proposed.

[0025] Firstly, a high-precision quantitative testing method for display module afterimages, such as... Figure 1 , Figure 1 This is a schematic diagram of a specific embodiment of a high-precision quantification test method for display module afterimages according to the present invention; including: In one possible implementation, before step 100, such as Figure 2 , Figure 2 for Figure 1 A schematic diagram of a specific implementation method prior to step 100; the method includes: Step 101: Set up a test environment that is compatible with the model of the display module and calibrate the brightness of the display module using the brightness standard reference value; Step 102: After the test environment is set up, drive the display module to display the preset stress duration.

[0026] In this embodiment, a darkroom testing environment is constructed to ensure that the ambient light intensity within the darkroom is ≤0.1 lux, the ambient temperature is controlled at 23±2℃, and the humidity is 50±5%RH. The display brightness of the display module under test is calibrated to the standard reference value L0. Typically, the preset stress duration T ranges from 1 to 12 hours, and the grayscale value of the uniform reference grayscale image is set to 128 or 192. When the display module under test is an organic light-emitting diode (OLED) display module, the preset stress duration T ranges from 2 to 24 hours, and the display area ratio of solid color blocks in the composite test image is not less than 30%.

[0027] Step 100: Construct a quantification model for afterimage level and drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least a red block, a green block, a blue block, and a white and yellow mixed color block.

[0028] In one possible implementation, such as Figure 3 , Figure 3 for Figure 1 A schematic diagram of a specific implementation of step 100; step 100 includes: Step 110: Classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into levels; Step 120: Construct a quantification model for afterimage level using the ranges of brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio after the level classification.

[0029] In this embodiment, a quantification model for determining the level of image retention is constructed. Specifically, the quantification model for determining the level of image retention is obtained by classifying the brightness attenuation rate R, brightness difference ΔL, chromaticity difference ΔE, and frequency domain energy ratio K into levels. It includes 4 levels, with the following preset threshold ranges: Level 1 (no afterimage): R≥98%, ΔL≤5cd / ㎡, ΔE≤1.5, K≤0.02; Level 2 (Slight Residual Image): 95%≤R<98%, 5cd / ㎡<ΔL≤10cd / ㎡, 1.5<ΔE≤3.0, 0.02<K≤0.05; Level 3 (moderate ghosting): 90%≤R<95%, 10cd / ㎡<ΔL≤20cd / ㎡, 3.0<ΔE≤5.0, 0.05<K≤0.1; Level 4 (Severe ghosting): R < 90%, ΔL > 20 cd / m², ΔE > 5.0, K > 0.1.

[0030] Step 200: Collect the time-domain data of the brightness image of the composite test screen, including the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area. Calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the brightness image data, and calculate the color deviation based on the actual color value parameters.

[0031] In one possible implementation, such as Figure 4 , Figure 4 for Figure 1 A schematic diagram of a specific implementation of step 200; step 200 includes: Step 210: Obtain the real-time brightness value and brightness standard reference value of the multi-level intermediate grayscale area, and obtain the stable brightness value of the multi-level intermediate grayscale area displayed for a specified time; Step 220: Calculate the brightness attenuation rate based on the brightness standard reference value, real-time brightness value and stable brightness value.

[0032] In this embodiment, the formula for calculating the luminance attenuation rate R is: R=[L(t)-L 稳定 ] / (L0-L 稳定 )×100% (1), Among them, L 稳定 L(t) represents the stable brightness value 30 minutes after the display module switches to a uniform reference grayscale image. It is the real-time brightness collected from the multi-level intermediate grayscale area.

[0033] In this embodiment, the grayscale value of the multi-level intermediate grayscale block area is between the maximum and minimum grayscale of the display module, and includes at least 4 different grayscale levels, one of which is consistent with the grayscale value of the uniform reference grayscale image.

[0034] In one possible implementation, such as Figure 5 , Figure 5 for Figure 4 A schematic diagram of a specific implementation following step 220; step 200 includes: step 230, acquiring the brightness values ​​of black squares and white squares in the black and white square area at the same time; step 240, calculating the brightness difference based on the brightness values ​​of black squares and white squares.

[0035] In this embodiment, the brightness difference ΔL is the brightness difference between corresponding positions in the black and white grid areas at the same acquisition time, that is: ΔL=|Lblack(t)-Lwhite(t)| (2) Where Lblack(t) is the real-time acquired brightness of the black grid, and Lwhite(t) is the real-time acquired brightness of the white grid.

[0036] In one possible implementation, such as Figure 6 , Figure 6 for Figure 5 A schematic diagram of a specific implementation following step 240; step 200 includes: step 250, acquiring the luminance component, red-green component, and yellow-blue component in the color region; step 260, calculating the luminance component difference ΔL*, red-green component difference Δa*, and yellow-blue component difference Δb* between the luminance component, red-green component, and yellow-blue component and the reference chromaticity, respectively; step 270, calculating the chromaticity deviation based on the luminance component difference ΔL*, red-green component difference Δa*, and yellow-blue component difference Δb*.

[0037] In this embodiment, the chromaticity deviation ΔE is calculated according to the CIELab color space formula: ΔE = [(Δa*) 2 +(Δb*) 2 +(ΔL*) 2 ] -1 / 2 (3) Perform calculations. Wherein, Δa*, Δb*, and ΔL* are the differences between the collected chromaticity data and the standard chromaticity data, respectively.

[0038] In one possible implementation, such as Figure 7 , Figure 7 for Figure 6 A schematic diagram of a specific implementation following step 270; step 200 includes: step 280, acquiring time-domain data of the brightness image, performing Fourier transform on the brightness image data to obtain frequency-domain data of the brightness image; step 290, extracting the first spectral energy value corresponding to the spatial frequency of the afterimage feature in the frequency-domain data of the brightness image, and obtaining the second spectral energy value of the uniform reference grayscale image spectrum; step 291, calculating the frequency domain energy ratio K based on the first spectral energy value and the second spectral energy value.

[0039] In this embodiment, a Fourier transform is performed on the acquired brightness image time-domain data to extract the first spectral energy value E1 corresponding to the afterimage characteristic frequency and the second spectral energy value E2 corresponding to the zero-frequency reference frequency. K = E1 / E2 is then calculated; the zero-frequency reference frequency is the reference frequency of the uniform reference grayscale image spectrum. When the display module under test is a liquid crystal display module, the afterimage characteristic frequency is the fundamental frequency of the spatial frequency of the black and white grid area; when the display module under test is an organic light-emitting diode display module, the afterimage characteristic frequency is the spatial frequency corresponding to the boundary of the multi-level intermediate grayscale block area.

[0040] Step 300: Obtain the image retention level quantification judgment model. Based on the calculated brightness attenuation rate, brightness difference, frequency domain energy ratio, and chromaticity deviation, use the image retention level quantification judgment model to quantify the image retention level of the display module.

[0041] In this embodiment, by constructing a quantification model for image retention levels, the display module under test is driven to display a composite test image. The model collects the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, the time domain data of the brightness image, and the actual color value parameters of the color area. Based on the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio and chromaticity deviation, the image retention level of the display module is quantified using the quantification model for image retention levels. This improves the accuracy of image retention determination and solves the problem that existing image retention detection methods are easily affected by environmental factors and detection bias, which leads to inaccurate detection results.

[0042] Secondly, a high-precision quantization testing device for display module afterimages employs the high-precision quantization testing method for display module afterimages from the first aspect, such as... Figure 8 , Figure 8 This is a schematic diagram illustrating a specific embodiment of a high-precision quantization testing device for display module afterimages according to the present invention. It includes: Module 401 is used to construct a quantitative judgment model for the afterimage level using the range of brightness attenuation rate, brightness difference range, chromaticity difference range and frequency domain energy ratio range. The driver module 402 is used to drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least a red block, a green block, a blue block, and a white and yellow mixed color block. The acquisition module 403 is used to acquire the time domain data of the brightness image of the composite test screen, the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area; The calculation module 404 is used to calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the time domain data of the brightness image, and calculate the color deviation based on the actual color value parameters. The quantization judgment module 405 is used to obtain the image retention level quantization judgment model. Based on the calculated brightness attenuation rate, brightness difference, frequency domain energy ratio and chromaticity deviation, the image retention level of the display module is quantified using the image retention level quantization judgment model.

[0043] In one possible implementation, the building module 401 includes: The division unit is used to classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into levels; the construction unit is used to construct a quantification judgment model of the afterimage level using the brightness attenuation rate range, brightness difference range, chromaticity difference range, and frequency domain energy ratio range after the level division.

[0044] In one possible implementation, the computing module 404 includes: The first calculation unit is used to calculate the brightness decay rate based on the brightness standard reference value, real-time brightness value and stable brightness value. The second calculation unit is used to calculate the brightness difference based on the brightness values ​​of the black squares and the brightness values ​​of the white squares. The third calculation unit is used to calculate the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity and the corresponding reference chromaticity, respectively, and to calculate the chromaticity deviation based on the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity. The fourth calculation unit is used to calculate the frequency domain energy ratio based on the first spectral energy value and the second spectral energy value.

[0045] The present invention provides a high-precision quantitative testing method and apparatus for display module afterimages. By constructing an afterimage level quantification judgment model, the display module under test displays a composite test image. It collects first brightness data from the black-and-white grid area, second brightness data from the multi-level intermediate grayscale area, time-domain data of the brightness image, and actual color value parameters of the color area. Based on the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio, and chromaticity deviation, the afterimage level quantification judgment model is used to quantify the afterimage level of the display module. This improves the accuracy of afterimage judgment and solves the problems of existing afterimage detection methods being susceptible to environmental influences and biased detection, leading to inaccurate results. The above are merely preferred embodiments of the present invention and are not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A high-precision quantitative testing method for display module afterimages, characterized in that it includes: Step 100: Construct a quantification model for the afterimage level using the range of brightness attenuation rate, brightness difference range, chromaticity difference range, and frequency domain energy ratio range, and drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least a red block, a green block, a blue block, and a white and yellow mixed color block. Step 200: Collect the time-domain data of the brightness image of the composite test screen, including the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area. Calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the brightness image data, and calculate the color deviation based on the actual color value parameters. Step 300: Obtain the image retention level quantization judgment model, and quantify the image retention level of the display module based on the calculated brightness attenuation rate, brightness difference, frequency domain energy ratio and chromaticity deviation using the image retention level quantization judgment model.

2. The high-precision quantitative testing method for display module afterimages according to claim 1, characterized in that, Prior to step 100, the method includes: Step 101: Set up a test environment that is compatible with the model of the display module and calibrate the brightness of the display module using the brightness standard reference value; Step 102: After the test environment is set up, drive the display module to display the preset stress duration.

3. The high-precision quantitative testing method for display module afterimages according to claim 1, characterized in that, Step 100 includes: Step 110: Classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into different levels; Step 120: Construct the afterimage level quantization judgment model by using the brightness attenuation rate range, brightness difference range, chromaticity difference range and frequency domain energy ratio range obtained by the level division.

4. The high-precision quantitative testing method for display module afterimages according to claim 3, characterized in that, Step 200 includes: Step 210: Obtain the real-time brightness value and brightness standard reference value of the multi-level intermediate grayscale region, and obtain the stable brightness value of the multi-level intermediate grayscale region displayed for a specified time. Step 220: Calculate the brightness attenuation rate based on the brightness standard reference value, the real-time brightness value, and the stable brightness value.

5. The high-precision quantitative testing method for display module afterimages according to claim 3, characterized in that, Step 200 includes: Step 230: Collect the brightness values ​​of the black squares and the white squares in the black and white square area at the same time. Step 240: Calculate the brightness difference based on the brightness values ​​of the black squares and the brightness values ​​of the white squares.

6. The high-precision quantitative testing method for display module afterimages according to claim 3, characterized in that, Step 200 includes: Step 250: Acquire the luminance component, red-green component, and yellow-blue component in the color region; Step 260: Calculate the differences between the luminance component, red-green component, and yellow-blue component and the reference chromaticity, respectively. Step 270: Calculate the chromaticity deviation based on the luminance component difference, red-green component difference, and yellow-blue component difference.

7. The high-precision quantitative testing method for display module afterimages according to claim 3, characterized in that, Step 200 includes: Step 280: Obtain the time domain data of the brightness image, and perform Fourier transform on the brightness image data to obtain the frequency domain data of the brightness image; Step 290: Extract the first spectral energy value corresponding to the spatial frequency of the afterimage feature in the brightness image frequency domain data, and obtain the second spectral energy value of the uniform reference grayscale image spectrum; Step 291: Calculate the frequency domain energy ratio based on the first spectral energy value and the second spectral energy value.

8. A high-precision quantization testing device for display module afterimages, employing the high-precision quantization testing method for display module afterimages as described in any one of claims 1-7, characterized in that, include: The module is used to construct a quantitative judgment model for the level of afterimage using the range of brightness attenuation rate, brightness difference range, chromaticity difference range, and frequency domain energy ratio range. The driving module is used to drive the display module under test to display a composite test screen. The composite test screen includes a black and white grid area, a multi-level intermediate grayscale area, and a color area. The color area includes at least a red block, a green block, a blue block, and a white and yellow mixed color block. The acquisition module is used to acquire the time-domain data of the brightness image of the composite test screen, the first brightness data of the black and white grid area, the second brightness data of the multi-level intermediate grayscale area, and the actual color value parameters of the color area; The calculation module is used to calculate the brightness difference based on the first brightness data, calculate the brightness attenuation rate based on the second brightness data, calculate the frequency domain energy ratio based on the time domain data of the brightness image, and calculate the color deviation based on the actual color value parameters. The quantization judgment module is used to obtain the afterimage level quantization judgment model, and quantify the afterimage level of the display module according to the calculated brightness attenuation rate and brightness difference, frequency domain energy ratio and chromaticity deviation, and the afterimage level quantization judgment model.

9. The high-precision quantification testing device for display module afterimages according to claim 8, characterized in that, The building module includes: The division unit is used to classify the brightness attenuation rate, brightness difference, chromaticity difference, and frequency domain energy ratio into levels; The construction unit is used to construct the afterimage level quantization judgment model by utilizing the brightness attenuation rate range, brightness difference range, chromaticity difference range and frequency domain energy ratio range after the level division.

10. The high-precision quantization testing device for display module afterimages according to claim 8, characterized in that, The computing module includes: The first calculation unit is used to calculate the brightness attenuation rate based on the brightness standard reference value, the real-time brightness value and the stable brightness value. The second calculation unit is used to calculate the brightness difference based on the brightness values ​​of the black squares and the brightness values ​​of the white squares. The third calculation unit is used to calculate the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity differences from the corresponding reference chromaticity, and to calculate the chromaticity deviation based on the red chromaticity, green chromaticity, blue chromaticity, and mixed chromaticity. The fourth calculation unit is used to calculate the frequency domain energy ratio based on the first spectral energy value and the second spectral energy value.

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