A method and device for quantifying color moire of a screen and a storage medium

Abstract

The application discloses a color moire quantification method and device of a screen and a storage medium, and is used for improving the elimination effect of color moire on the screen. A sub-pixel brightness graph of a to-be-compensated screen in different pixel channels is acquired; a compensation effect graph is generated according to the sub-pixel brightness graph; the compensation effect graph is subjected to color space conversion to generate the compensation effect graph in an anaglyph space; the compensation effect graph in the anaglyph space is filtered by using a contrast sensitivity function to generate a spectral image of each pixel channel; the spectral image of each pixel channel is subjected to human eye visual segmentation processing to generate a plurality of fan-shaped segmentation areas; and a color moire quantification index of the compensation effect graph is generated according to the pixel contrast and the direction factor of the plurality of fan-shaped segmentation areas.

Description

Technical Field

[0001] This application relates to the field of moiré patterns, and more particularly to a method, apparatus, and storage medium for quantifying color moiré patterns on a screen. Background Technology

[0002] With technological innovation, new display technologies are constantly being updated and iterated. As a core link in the display industry chain, display quality inspection technology continues to receive attention, especially the detection of Mura defects at the micron level on the display surface, which has become a key factor determining the quality of display products. Optical Demura systems use high-resolution industrial cameras to capture images of illuminated displays and extract sub-pixel brightness images from the captured images. This allows for the detection of Mura defects on the panel, enabling high-precision color / brightness compensation, thereby optimizing display quality and improving yield.

[0003] However, when the spatial frequency of the pixels of the color camera's image sensor is close to the spatial frequency of the pixels of the display screen to be compensated, the frequency beat effect between the color camera pixels and the display pixels will cause moiré defects, resulting in distortion of the subpixel brightness map. Color moiré will appear on the screen to be compensated after Demura compensation. The higher the pixel density and the more precise the hierarchical structure of the display screen to be compensated, the easier it is to detect these color moiré patterns.

[0004] In OLED screen manufacturing, the degree of moiré pattern on the compensation back panel is typically evaluated manually. This process is very time-consuming and requires experienced observers. Existing methods for quantizing color moiré patterns in screens primarily target moiré patterns caused by interference between the screen's stacked structures. Therefore, these methods do not consider the influence of the display signal on the calculation of the moiré quantization index, nor do they take into account the directional sensitivity of the human visual system. This leads to decreased quantization accuracy for color moiré patterns, thereby reducing the effectiveness of color moiré pattern elimination on the screen. Summary of the Invention

[0005] This application discloses a method, apparatus, and storage medium for quantifying color moiré patterns on a screen, which improves the elimination effect of color moiré patterns on the screen.

[0006] In a first aspect, embodiments of this application provide a method for quantifying color moiré patterns on a screen, comprising:

[0007] Obtain the sub-pixel brightness maps of the screen to be compensated in different pixel channels;

[0008] Generate a compensation effect map based on the sub-pixel brightness map;

[0009] Perform color space conversion on the compensation effect image to generate a compensation effect image in the opposite color space;

[0010] The contrast sensitivity function is used to filter the compensation effect map in the opposing color space to generate the spectrum image of each pixel channel;

[0011] The spectral images of each pixel channel are processed by human visual segmentation to generate several fan-shaped segmentation regions;

[0012] The color moiré quantization index is generated based on the pixel contrast and orientation factor of several sector-divided regions to create the compensation effect map.

[0013] Optionally, the step of generating the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of several sector-divided regions specifically includes:

[0014] Obtain the contrast threshold and weight parameters for different color channels based on the display characteristics of the screen to be compensated;

[0015] The color moiré quantization index of the compensation effect map is generated based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of several sector segmentation regions, and the orientation factor.

[0016] Optionally, after performing human visual segmentation processing on the spectral images of each pixel channel to generate several fan-shaped segmented regions, and before generating the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of the several fan-shaped segmented regions, the quantization method further includes:

[0017] Determine the spatial frequency, orientation angle, and pixel standard deviation of the moiré component at the center position of each sector segmentation region;

[0018] Calculate the pixel contrast of each sector segment based on the pixel standard deviation of each sector segment in the current annulus;

[0019] Calculate the frequency-related directional coefficient based on the spatial frequency of the moiré component corresponding to the center position;

[0020] The directional factors of several sector-shaped segmented regions are generated based on the directional coefficient and the directional angle of the moiré component corresponding to the center position.

[0021] Optionally, color space conversion includes non-screen-dependent color space conversion and contrasting color space conversion;

[0022] The specific steps for converting the compensation effect image to a color space to generate a compensation effect image in an opposing color space include:

[0023] The compensation effect image is converted to a non-screen-dependent color space, which transforms the compensation effect image from a color space related to the screen device under test to a color space unrelated to the screen device under test.

[0024] The compensation effect image in the color space related to the non-test screen device is converted to an opposite color space to generate a compensation effect image in the opposite color space.

[0025] Optionally, the step of filtering the compensation effect map in the contrasting color space using a contrast sensitivity function to generate the spectral image of each pixel channel specifically includes:

[0026] Contrast sensitivity function is constructed based on the spatial frequency of the compensation effect map in the opposite color space and the channel fitting parameters.

[0027] The spectrum image of each pixel channel is generated based on the contrast sensitivity function and the compensation effect map in the opposite color space.

[0028] Optionally, the steps of obtaining the sub-pixel brightness maps of the screen to be compensated in different pixel channels specifically include:

[0029] Create a pixel positioning map and a grayscale map based on the screen to be compensated;

[0030] The pixel positioning map and grayscale map are input into the screen to be compensated, and the image is acquired by an industrial camera to generate the positioning acquisition image and grayscale acquisition image.

[0031] By locating the channel pixels of the grayscale acquired image, sub-pixel brightness maps of different pixel channels are generated.

[0032] Optionally, the steps for generating the compensation effect map based on the sub-pixel brightness map specifically include:

[0033] A compensation effect map is generated based on the brightness maps of sub-pixels of adjacent gray levels.

[0034] Secondly, embodiments of this application provide a device for quantizing color moiré patterns on a screen, comprising:

[0035] The subpixel brightness map acquisition unit is used to acquire the subpixel brightness maps of the screen to be compensated in different pixel channels.

[0036] The compensation effect map generation unit is used to generate a compensation effect map based on the sub-pixel brightness map.

[0037] The color space conversion unit is used to convert the color space of the compensation effect image and generate a compensation effect image in the opposite color space.

[0038] The spectrum image generation unit is used to filter the compensation effect map in the opposing color space using a contrast sensitivity function to generate spectrum images for each pixel channel.

[0039] The human visual segmentation processing unit is used to perform human visual segmentation processing on the spectral image of each pixel channel to generate several fan-shaped segmentation regions.

[0040] The color moiré quantization index generation unit is used to generate the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of several sector-divided regions.

[0041] Optionally, the color moiré quantization index generation unit specifically includes:

[0042] Obtain the contrast threshold and weight parameters for different color channels based on the display characteristics of the screen to be compensated;

[0043] The color moiré quantization index of the compensation effect map is generated based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of several sector segmentation regions, and the orientation factor.

[0044] Optionally, after the human visual segmentation processing unit and before the color moiré quantization index generation unit, the quantization device further includes:

[0045] The sector segmentation region parameter determination unit is used to determine the spatial frequency, orientation angle, and pixel standard deviation of the moiré component corresponding to the center position of each sector segmentation region.

[0046] The pixel contrast calculation unit is used to calculate the pixel contrast of each sector segment based on the pixel standard deviation of each sector segment within the current annulus.

[0047] Direction coefficient calculation unit, used to calculate frequency-related direction coefficients based on the spatial frequency of the moiré component corresponding to the center position;

[0048] The orientation factor generation unit is used to generate orientation factors for several sector-shaped segmented regions based on the orientation coefficient and the orientation angle of the moiré component corresponding to the center position.

[0049] Optionally, color space conversion includes non-screen-dependent color space conversion and contrasting color space conversion;

[0050] The color space conversion unit specifically includes:

[0051] The compensation effect image is converted to a non-screen-dependent color space, which transforms the compensation effect image from a color space related to the screen device under test to a color space unrelated to the screen device under test.

[0052] The compensation effect image in the color space related to the non-test screen device is converted to an opposite color space to generate a compensation effect image in the opposite color space.

[0053] Optionally, the spectrum image generation unit specifically includes:

[0054] Contrast sensitivity function is constructed based on the spatial frequency of the compensation effect map in the opposite color space and the channel fitting parameters.

[0055] The spectrum image of each pixel channel is generated based on the contrast sensitivity function and the compensation effect map in the opposite color space.

[0056] Optionally, the sub-pixel brightness map acquisition unit specifically includes:

[0057] Create a pixel positioning map and a grayscale map based on the screen to be compensated;

[0058] The pixel positioning map and grayscale map are input into the screen to be compensated, and the image is acquired by an industrial camera to generate the positioning acquisition image and grayscale acquisition image.

[0059] By locating the channel pixels of the grayscale acquired image, sub-pixel brightness maps of different pixel channels are generated.

[0060] Optionally, the compensation effect diagram generation unit specifically includes:

[0061] A compensation effect map is generated based on the brightness maps of sub-pixels of adjacent gray levels.

[0062] Thirdly, embodiments of this application provide a device for quantizing color moiré patterns on a screen, comprising:

[0063] Processor, memory, input / output units, and bus;

[0064] The processor is connected to memory, input / output units, and a bus;

[0065] The memory stores a program, which the processor calls to execute, such as the first aspect and any optional quantization method of the first aspect.

[0066] Fourthly, embodiments of this application provide a computer-readable storage medium on which a program is stored, which, when executed on a computer, performs the first aspect and any optional quantization method of the first aspect.

[0067] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0068] In this application, firstly, sub-pixel brightness maps of the screen to be compensated in different pixel channels are obtained. A compensation effect map is generated based on the sub-pixel brightness maps. The compensation effect map is then color-space converted to generate a compensation effect map in an opposing color space. A contrast sensitivity function is used to filter the compensation effect map in the opposing color space, generating a spectral image for each pixel channel. The spectral images of each pixel channel are then processed using human visual segmentation to generate several fan-shaped segmented regions. Finally, a color moiré quantization index for the compensation effect map is generated based on the pixel contrast and orientation factor of the several fan-shaped segmented regions.

[0069] Demura compensation is performed on the sub-pixel brightness maps of each color channel of the screen to be compensated, which are then converted into compensation effect maps and further converted into spectrum images. Next, the spectrum image is segmented based on human visual perception. For each segmented sector, pixel contrast and orientation factors are calculated. Then, a color moiré quantization index for the screen to be compensated is generated using the pixel contrast and orientation factors of each sector. This method not only considers the influence of the display signal on the moiré quantization index calculation, but also integrates visual segmentation using the human visual system, and incorporates the orientation sensitivity of each segmented region for color moiré quantization, thereby improving the accuracy of color moiré quantization and thus improving the elimination effect of color moiré on the screen. Attached Figure Description

[0070] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 This is a schematic diagram of the first embodiment of the method for quantizing the color moiré pattern on the screen according to this application;

[0072] Figure 2 A schematic diagram of a first embodiment of the method for generating a color moiré quantization index according to this application;

[0073] Figure 3 A schematic diagram of a first embodiment of the method for generating pixel contrast and orientation factor according to this application;

[0074] Figure 4 A schematic diagram of a first embodiment of the method for generating a compensation effect diagram in an opposing color space according to this application;

[0075] Figure 5 A schematic diagram of a first embodiment of the method for generating a spectral image of pixel channels according to this application;

[0076] Figure 6 This is a schematic diagram of a first embodiment of the method for generating a subpixel brightness map according to this application;

[0077] Figure 7 A schematic diagram of a first embodiment of the method for generating compensation effect diagrams for this application;

[0078] Figure 8 This is a schematic diagram of the first embodiment of the color moiré quantization device for the screen of this application;

[0079] Figure 9 This is a schematic diagram of the image processing flow in the color moiré quantization of this application;

[0080] Figure 10 This is a diagram showing the compensation effect before CSF function filtering in this application;

[0081] Figure 11 This is a diagram showing the compensation effect after filtering using the CSF function in this application;

[0082] Figure 12 This is a schematic diagram of the applicant's visual segmentation.

[0083] Figure 13 This is a schematic diagram of the moiré peak detection method in this application;

[0084] Figure 14 This is a schematic diagram of the colored moiré pattern in different compensation effect diagrams of this application;

[0085] Figure 15 This is a comparison chart of the subjective and quantitative values ​​of 30 normal compensation effect diagrams in this application;

[0086] Figure 16 This is a comparison of the subjective values ​​and quantization values ​​of 15 images containing moiré patterns in a single channel, based on this application. Detailed Implementation

[0087] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0088] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0089] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0090] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0091] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0092] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0093] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0094] The method described in this application can be applied to servers, devices, terminals, or other devices with logical processing capabilities; therefore, this application does not limit its application. For ease of description, the following description uses a terminal as the executing entity.

[0095] Please see Figure 1 This application provides an embodiment of a method for quantifying color moiré patterns on a screen, comprising:

[0096] 101. Obtain the sub-pixel brightness map of the screen to be compensated in different pixel channels;

[0097] In this embodiment, the terminal first acquires detection images of the screen under test at different gray levels through the camera, and then separates the pixel channels of the detection images to generate sub-pixel brightness maps of different pixel channels. The specific sub-pixel brightness map generation method will be described in detail in subsequent embodiments.

[0098] 102. Generate a compensation effect image based on the sub-pixel brightness image;

[0099] In this embodiment, after the terminal obtains the sub-pixel brightness maps of different pixel channels, it needs to use the OLEDDemura system to perform Demura compensation processing on the sub-pixel brightness maps of different pixel channels so as to obtain an image that can display the compensation effect. The specific method of generating the compensation effect map will be described in detail in subsequent embodiments.

[0100] 103. Perform color space conversion on the compensation effect image to generate a compensation effect image in the opposite color space;

[0101] In this embodiment, the terminal performs color space conversion on the compensation effect image, specifically including conversion of the relevant color space of the display to be compensated and conversion of the opposing color space. When the same group of R / G / B sub-pixel brightness images are displayed on different screen devices, the resulting color effects will differ. Even after compensation, differences will still exist depending on the screen device; therefore, color space conversion is necessary. The purpose of opposing color space conversion is to concentrate most of the energy on the brightness channel and reduce the correlation between channels, thereby improving the accuracy of subsequent color moiré quantization. Specific color space conversion methods will be described in detail in subsequent embodiments.

[0102] 104. Use the contrast sensitivity function to filter the compensation effect image in the contrasting color space to generate the spectrum image of each pixel channel;

[0103] The terminal obtains the contrast sensitivity function and uses it to filter the compensation effect image in the contrast color space, generating a corresponding spectrum image for each pixel channel. This greatly reduces the high-frequency moiré components in the compensation effect image in the contrast color space, resulting in higher quantization accuracy of the subsequent color moiré. The specific use of the contrast sensitivity function to filter the compensation effect image in the contrast color space will be described in detail in the following embodiments.

[0104] 105. Perform human visual segmentation processing on the spectral image of each pixel channel to generate several fan-shaped segmentation regions;

[0105] In this embodiment, to assess the directional sensitivity of the human visual system, the terminal performs visual segmentation processing on the spectral images of each pixel channel, generating several fan-shaped segmentation regions. Because the spatial frequencies within each ring are very close, the standard deviations of different sectors within the same ring are also relatively close. This facilitates identifying sectors containing moiré peaks based on their contrast within the ring. Furthermore, for subsequent segmentation based on directional sensitivity, the human eye is more sensitive to horizontal / vertical stripes in the brightness channel than to diagonal stripes. Using fan-shaped regions in this embodiment better incorporates the directional sensitivity of the human eye. Please refer to [reference needed]. Figure 12 , Figure 12 The diagram illustrates human visual segmentation. It requires generating sector angles and radius lengths based on the screen parameters and characteristics of the screen to be compensated, and in conjunction with the sensitivity of human visual perception, so that the contrast calculation results of each sector area are more accurate.

[0106] The process for calculating the moiré quantization index in this embodiment is as follows: Figure 9 As shown, the terminal uses the compensation effect image or a local image patch cropped from the compensation effect image as the input image. After converting the input image to the contrasting color space, a two-dimensional discrete Fourier transform is performed on each color channel, followed by spectral centering to generate a spectral image. Then, the terminal performs a bitwise multiplication of the spectral image of the corresponding color channel with the contrast sensitivity function to obtain the spectral image filtered by the contrast sensitivity function. The moiré quantization index is calculated based on the filtered spectral images of the three color channels.

[0107] 106. Generate the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of several sector-divided regions.

[0108] After the terminal completes the human visual segmentation processing, it needs to obtain the pixel contrast and orientation factor of several sector segmentation regions. Then, based on the pixel contrast and orientation factor of several sector segmentation regions, it generates the color moiré quantization index of the compensation effect map. The specific calculation method of the color moiré quantization index will be described in detail in subsequent embodiments.

[0109] In this embodiment, firstly, sub-pixel brightness maps of the screen to be compensated in different pixel channels are obtained. A compensation effect map is generated based on the sub-pixel brightness maps. The compensation effect map is then color-space converted to generate a compensation effect map in an opposing color space. A contrast sensitivity function is used to filter the compensation effect map in the opposing color space, generating a spectral image for each pixel channel. The spectral images of each pixel channel are then processed using human visual segmentation to generate several fan-shaped segmented regions. Based on the pixel contrast and orientation factor of these fan-shaped segmented regions, a color moiré quantization index for the compensation effect map is generated.

[0110] Demura compensation is performed on the sub-pixel brightness maps of each color channel of the screen to be compensated, which are then converted into compensation effect maps and further converted into spectrum images. Next, the spectrum image is segmented based on human visual perception. For each segmented sector, pixel contrast and orientation factors are calculated. Then, a color moiré quantization index for the screen to be compensated is generated using the pixel contrast and orientation factors of each sector. This method not only considers the influence of the display signal on the moiré quantization index calculation, but also integrates visual segmentation using the human visual system, and incorporates the orientation sensitivity of each segmented region for color moiré quantization, thereby improving the accuracy of color moiré quantization and thus improving the elimination effect of color moiré on the screen.

[0111] Please see Figure 2 This application provides an embodiment of a method for generating a colored moiré quantization index, comprising:

[0112] 201. Obtain the contrast threshold and weight parameters for different color channels based on the display characteristics of the screen to be compensated;

[0113] 202. Generate the color moiré quantization index of the compensation effect map based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of several sector segmentation regions, and the orientation factor.

[0114] In this embodiment, the terminal obtains the contrast threshold and weight parameters of different color channels based on the display characteristics of the screen to be compensated. Then, based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of several sector-divided regions, and the orientation factor, it generates the color moiré quantization index of the compensation effect map. Specifically, the calculation formula for the moiré quantization index can be expressed as:

[0115]

[0116] Where t represents the contrast threshold parameter, The preset quantization constant, These are the weight parameters for channel i. Please refer to [link / reference]. Figure 13 , Figure 13 This is a schematic diagram of moiré peak detection. When the spectral amplitude diagram satisfies... The set of sector-shaped regions, such as Figure 13 As shown, sector regions that do not meet the threshold condition are set to 0. This algorithm only accumulates the contrast of sectors detected using a fixed threshold t after direction weighting, and these sectors contain one or more moiré peaks. Since the human visual system's perception of opposing color spaces is not uniform, the formula not only uses pixel contrast and direction factors, but also takes the 2.2th root of the summation value to further improve the uniformity of the calculated moiré index in human perception.

[0117] The effects of the color moiré quantization method of this application are described below:

[0118] This embodiment involved experimental testing. The experiment used a 151M color camera with a Bayer filter and multiple mobile phones of different models to obtain a series of compensation effect images. The camera's focus, rotation angle relative to the screen under test, and working distance were adjusted to ensure that the moiré patterns in these compensation effect images covered various directions, frequencies, and contrasts. Please refer to... Figure 14 , Figure 14 These are schematic diagrams illustrating the color moiré pattern in different compensation effect images. Figure 14 The image shows several color moiré patterns in the generated images with different compensation effects. Next, the experiment uses a DUT display device to display the resolution (2400) of the image cropped to that DUT display device. Compensation effect images of size 1176. A total of 45 compensation effect images were used in the experiment. Among them, 30 images are normal compensation effect images, with moiré patterns in all three color channels. The remaining 15 images are images where moiré patterns were eliminated by global mean filtering of two color channels in the three-color channel effect images, leaving only one color channel with moiré patterns. The gray values ​​of each image were normalized so that the gray mean of the central region of each channel of the image is equal to the target gray level value.

[0119] Eleven visually normal observers were randomly selected for the experiment to rate the severity of moiré patterns in each image displayed on the DUT (Display Under Test) device. The experiment was conducted in a dark room, with the viewing distance fixed at 18 cm using a chin rest and a phone stand. Each observer viewed 45 compensated images in a different random order and rated the severity of moiré patterns on a scale of 0-10 (0 for no moiré patterns, 10 for the most severe). The observer's average score for each image was used as a subjective value and compared with a calculated moiré pattern quantification index. Please refer to [reference needed]. Figure 15 and Figure 16 , Figure 15 This is a comparison chart of the subjective and quantitative values ​​of 30 normal compensation effect images. Figure 16 This image shows a comparison of subjective values ​​and quantized values ​​for 15 images containing moiré patterns in only one channel. Figure 15 and Figure 16 The relationship between subjective values ​​and quantization indices is shown for 30 normally compensated images and 15 images after filtering. The figures show a strong linear positive correlation between subjective values ​​and moiré quantization values. The Pearson correlation coefficient calculated from the subjective values ​​and quantization indices of all 45 images is r = 0.9042, indicating that the moiré quantization algorithm proposed in this embodiment can accurately reflect the severity of color moiré patterns.

[0120] Please see Figure 3 This application provides an embodiment of a method for generating pixel contrast and orientation factors, comprising:

[0121] 301. Determine the spatial frequency, orientation angle, and pixel standard deviation of the moiré component at the center position of each sector segmentation region;

[0122] 302. Calculate the pixel contrast of each sector segment based on the pixel standard deviation of each sector segment within the current annulus.

[0123] 303. Calculate the frequency-dependent directional coefficient based on the spatial frequency of the moiré component corresponding to the center position;

[0124] 304. Generate direction factors for several sector-shaped segmented regions based on the direction coefficient and the direction angle of the moiré component corresponding to the center position.

[0125] In this embodiment, the terminal first decomposes the spectral images of each color channel to generate corresponding spectral amplitude images. Then, it segments the frequency domain space with fixed radial and angular step sizes, and calculates the pixel standard deviation of the spectral amplitude image in each segmented sector region. An example of segmentation is shown below. Figure 12 As shown. Within each sector's annulus, the contrast of each sector within the annulus is calculated based on the pixel standard deviation of each sector. Where i represents the color channel number, and These represent the spatial frequency and orientation angle of the moiré component corresponding to the center position of the current sector region. Since the sensitivity of the human visual system is related to the orientation of the visual pattern, and exhibits different directional characteristics at different frequencies in different channels, this embodiment constructs an orientation factor, as follows:

[0126]

[0127] in This represents the direction factor related to the spatial frequency u in the i-th color channel. The direction factor calculated in this way can better integrate the influence of the display signal on the calculation of the moiré quantization index, while also taking into account the direction sensitivity of the human visual system.

[0128] Please see Figure 4 This application provides an embodiment of a method for generating a compensation effect map in an opposing color space. The color space conversion includes non-screen-dependent color space conversion and opposing color space conversion, including:

[0129] 401. Perform non-screen-dependent color space conversion on the compensation effect image to convert the compensation effect image from the color space related to the screen device under test to a color space unrelated to the screen device under test. Non-screen-dependent color space conversion is used to convert the compensation effect image to a color space that is unrelated to the current screen device under test.

[0130] The compensation effect image generated in step 102 is located in the RGB color space related to the screen device to be compensated. In order to improve the stability of the color moiré quantization algorithm in this embodiment, the terminal needs to convert the compensation effect image to a color space unrelated to the current screen device to be compensated for the quantization value calculation.

[0131] Specifically, the terminal first converts the compensation effect map to the CIE XYZ space, using the following formula:

[0132]

[0133] in, This represents the CIE X value contributed by the red primary color (red channel) of the panel under test under the preset grayscale level g-drive, that is, the X value measured by a colorimeter when the screen to be compensated is lit with red monochrome at the g grayscale level. It is the gamma value of the red channel of the screen to be compensated. The gamma is obtained in advance by fitting the brightness values ​​of multiple gray levels measured by a colorimeter for each color channel. The definitions of other parameters can be deduced in the same way, and will not be elaborated here.

[0134] 402. Convert the compensation effect image in the color space related to the non-test screen device to the opposite color space to generate a compensation effect image in the opposite color space.

[0135] Next, the terminal transforms the compensation image in the CIE XYZ color space to the opposite color space using a linear transformation, where... For the luminance channel, For traffic lights and green lanes, The yellow and blue channels are used. The terminal converts the compensation effect image to an opposing color space to concentrate most of the energy in the luminance channel and reduce the correlation between channels. A linear transformation is performed on the compensation effect image in the CIE XYZ chromaticity space to obtain the compensation effect image in the opposing color space. After the transformation, the energy proportion of the first channel is significantly higher than that of the original channels, and the absolute value of the cross-correlation coefficients between the channels after the transformation is significantly lower than that of the original channels. Furthermore, the linear transformation designed based on the luminance-chromaticity opposing color principle (the first channel mainly consists of luminance information, while the second and third channels mainly consist of chromaticity opposing information) all belong to the luminance channel described in this embodiment. Red and green channels Yellow and Blue Channel The equivalent transformation of opposing color spaces is shown in the following formula:

[0136]

[0137] Please see Figure 5 This application provides an embodiment of a method for generating a spectral image of pixel channels, comprising:

[0138] 501. Construct a contrast sensitivity function based on the spatial frequency of the compensation effect map in the opposing color space and the channel fitting parameters;

[0139] 502. Generate the spectral image of each pixel channel based on the contrast sensitivity function and the compensation effect map in the opposite color space.

[0140] In this embodiment, due to differences in pixel arrangement and pixel spacing on the screens to be compensated, the same compensated image often exhibits different degrees of color moiré when displayed on different screens. To take this factor into account, this embodiment uses a contrast sensitivity function to filter the compensated image in the opposing color space. For details, please refer to... Figure 9 , Figure 9 This diagram illustrates the image processing flow in color moiré quantization. First, the compensation image in the contrasting color space needs to be converted into a frequency domain image. The contrast sensitivity function models the contrast sensitivity of the human visual system as a function of spatial frequency. Please refer to [reference needed]. Figure 10 and Figure 11 , Figure 10 and Figure 11 The images show partial schematic diagrams of the compensation effect diagram with moiré patterns (compensation effect diagram before CSF function filtering) and schematic diagrams of the output results after contrast sensitivity function filtering (compensation effect diagram after CSF function filtering). It can be seen that contrast sensitivity function filtering significantly reduces the high-frequency moiré components in the compensation effect diagram.

[0141] The contrast sensitivity function describes the frequency sensitivity characteristics of the human visual system. The CSF function, which accurately reflects the visual sensitivity characteristics of each channel in the contrasting color space, is used to filter the compensation image. The constructed contrast sensitivity function is shown below:

[0142]

[0143]

[0144]

[0145] Where u represents spatial frequency, with units of cycles per degree, and a, b, and c are parameters fitted to each color channel based on measured values ​​from psychophysical experiments. In this embodiment, the CSF function of each color channel is represented as a 2D image.

[0146] Please see Figure 6 This application provides an embodiment of a method for generating a subpixel brightness map, comprising:

[0147] 601. Create a pixel positioning map and a grayscale map based on the screen to be compensated;

[0148] 602. Input the pixel positioning map and grayscale map into the screen to be compensated, and acquire the image through an industrial camera to generate the positioning acquisition image and grayscale acquisition image;

[0149] 603. Locate the channel pixels of the grayscale acquired image by positioning the acquired image, and generate sub-pixel brightness maps of different pixel channels.

[0150] In this embodiment, the terminal creates corresponding pixel positioning maps and grayscale maps based on the characteristics of the screen to be compensated. The pixel positioning maps are divided into pixel positioning maps for different channels, specifically including R pixel positioning maps, G pixel positioning maps, and B pixel positioning maps. The grayscale maps are designed based on the grayscale levels required by the screen to be compensated, and several images with different grayscale levels can be designed.

[0151] The terminal will use grayscale The pixel positioning map is sequentially input into the display screen to be compensated. An industrial camera is used in a dark room to capture images of the screen to be compensated, generating positioning acquisition images and grayscale acquisition images.

[0152] The Demura algorithm and localized image acquisition methods are used to locate sub-pixels in the R, G, and B color channels of each grayscale acquisition image, and the brightness information of the sub-pixels is extracted to generate grayscale values. The R subpixel brightness map, G subpixel brightness map, and B subpixel brightness map.

[0153] Please see Figure 7 This application provides an embodiment of a method for generating compensation effect diagrams, comprising:

[0154] 701. Generate a compensation effect map based on the sub-pixel brightness maps of adjacent gray levels.

[0155] In this embodiment, the terminal needs to determine the grayscale level. The R subpixel brightness map, G subpixel brightness map, and B subpixel brightness map generate grayscale. The compensation effect diagram. Specifically, the terminal calculates the compensation effect based on two adjacent gray levels. , ( Subpixel brightness map , calculate Grayscale compensation effect diagram The formula is as follows:

[0156]

[0157] Please see Figure 8 This application provides an embodiment of a device for quantizing color moiré patterns on a screen, comprising:

[0158] The subpixel brightness map acquisition unit 801 is used to acquire the subpixel brightness maps of the screen to be compensated in different pixel channels.

[0159] The compensation effect map generation unit 802 is used to generate a compensation effect map based on the sub-pixel brightness map.

[0160] Color space conversion unit 803 is used to perform color space conversion on the compensation effect image to generate a compensation effect image in the opposite color space.

[0161] The spectrum image generation unit 804 is used to filter the compensation effect map in the opposite color space using a contrast sensitivity function to generate spectrum images for each pixel channel.

[0162] The human visual segmentation processing unit 805 is used to perform human visual segmentation processing on the spectral image of each pixel channel to generate several fan-shaped segmentation regions.

[0163] The color moiré quantization index generation unit 806 is used to generate the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of several sector segmented regions.

[0164] Optionally, the color moiré quantization index generation unit 806 specifically includes:

[0165] Obtain the contrast threshold and weight parameters for different color channels based on the display characteristics of the screen to be compensated;

[0166] The color moiré quantization index of the compensation effect map is generated based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of several sector segmentation regions, and the orientation factor.

[0167] Optionally, after the human visual segmentation processing unit 805 and before the color moiré quantization index generation unit 806, the quantization device further includes:

[0168] The sector segmentation region parameter determination unit is used to determine the spatial frequency, orientation angle, and pixel standard deviation of the moiré component corresponding to the center position of each sector segmentation region.

[0169] The pixel contrast calculation unit is used to calculate the pixel contrast of each sector segment based on the pixel standard deviation of each sector segment within the current annulus.

[0170] Direction coefficient calculation unit, used to calculate frequency-related direction coefficients based on the spatial frequency of the moiré component corresponding to the center position;

[0171] The orientation factor generation unit is used to generate orientation factors for several sector-shaped segmented regions based on the orientation coefficient and the orientation angle of the moiré component corresponding to the center position.

[0172] Optionally, color space conversion includes non-screen-dependent color space conversion and contrasting color space conversion;

[0173] The color space conversion unit 803 specifically includes:

[0174] The compensation effect image is converted to a non-screen-dependent color space, which transforms the compensation effect image from a color space related to the screen device under test to a color space unrelated to the screen device under test.

[0175] The compensation effect image in the color space related to the non-test screen device is converted to an opposite color space to generate a compensation effect image in the opposite color space.

[0176] Optionally, the spectrum image generation unit 804 specifically includes:

[0177] Contrast sensitivity function is constructed based on the spatial frequency of the compensation effect map in the opposite color space and the channel fitting parameters.

[0178] The spectrum image of each pixel channel is generated based on the contrast sensitivity function and the compensation effect map in the opposite color space.

[0179] Optionally, the sub-pixel brightness map acquisition unit 801 specifically includes:

[0180] Create a pixel positioning map and a grayscale map based on the screen to be compensated;

[0181] The pixel positioning map and grayscale map are input into the screen to be compensated, and the image is acquired by an industrial camera to generate the positioning acquisition image and grayscale acquisition image.

[0182] By locating the channel pixels of the grayscale acquired image, sub-pixel brightness maps of different pixel channels are generated.

[0183] Optionally, the compensation effect diagram generation unit 802 specifically includes:

[0184] A compensation effect map is generated based on the brightness maps of sub-pixels of adjacent gray levels.

[0185] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0186] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0187] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0188] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0189] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for quantifying color moiré patterns on a screen, characterized in that, include: Obtain the sub-pixel brightness maps of the screen to be compensated in different pixel channels; A compensation effect map is generated based on the sub-pixel brightness map; The compensation effect image is converted to a color space to generate a compensation effect image in an opposing color space; The compensation effect image in the opposing color space is filtered using a contrast sensitivity function to generate a spectral image for each pixel channel. The spectral images of each pixel channel are processed by human visual segmentation to generate several fan-shaped segmentation regions; The color moiré quantization index of the compensation effect map is generated based on the pixel contrast and orientation factor of the several sector segmentation regions.

2. The quantization method according to claim 1, characterized in that, The step of generating the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of the plurality of sector segmentation regions specifically includes: The contrast threshold and weight parameters for different color channels are obtained based on the display characteristics of the screen to be compensated. The color moiré quantization index of the compensation effect map is generated based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of the several sector segmentation regions, and the orientation factor.

3. The quantization method according to claim 2, characterized in that, After the step of performing human visual segmentation processing on the spectral images of each pixel channel to generate several fan-shaped segmented regions, and before the step of generating the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of the several fan-shaped segmented regions, the quantization method further includes: Determine the spatial frequency, orientation angle, and pixel standard deviation of the moiré component at the center position of each sector segmentation region; Calculate the pixel contrast of each sector segment based on the pixel standard deviation of each sector segment in the current annulus; Calculate the frequency-related directional coefficient based on the spatial frequency of the moiré component corresponding to the center position; The direction factors of the several sector-shaped segmented regions are generated based on the direction coefficient and the direction angle of the moiré component corresponding to the center position.

4. The quantization method according to claim 1, characterized in that, The color space conversion includes non-screen-dependent color space conversion and contrasting color space conversion; The step of performing color space conversion on the compensation effect image to generate a compensation effect image in an opposing color space specifically includes: The compensation effect image is converted to a non-screen-dependent color space, which converts the compensation effect image from a color space related to the screen device under test to a color space unrelated to the screen device under test. The non-screen-dependent color space conversion is used to convert the compensation effect image to a color space that is unrelated to the current screen device under test. The compensation effect image in the color space related to the non-test screen device is converted to an opposite color space to generate a compensation effect image in the opposite color space.

5. The quantization method according to claim 1, characterized in that, The step of filtering the compensation effect image in the opposing color space using a contrast sensitivity function to generate the spectral image of each pixel channel specifically includes: A contrast sensitivity function is constructed based on the spatial frequency of the compensation effect diagram in the opposing color space and the channel fitting parameters. The spectral image of each pixel channel is generated based on the contrast sensitivity function and the compensation effect map in the opposing color space.

6. The quantization method according to any one of claims 1 to 5, characterized in that, The step of obtaining the sub-pixel brightness maps of the screen to be compensated in different pixel channels specifically includes: Create a pixel positioning map and a grayscale map based on the screen to be compensated; The pixel positioning map and the grayscale map are respectively input into the screen to be compensated, and the image is acquired by an industrial camera to generate a positioning acquisition image and a grayscale acquisition image. The grayscale image is located by positioning the acquired image to generate sub-pixel brightness maps for different pixel channels.

7. The quantization method according to any one of claims 1 to 5, characterized in that, The step of generating the compensation effect map based on the sub-pixel brightness map specifically includes: A compensation effect map is generated based on the brightness maps of the sub-pixels of adjacent gray levels.

8. A device for quantizing color moiré patterns on a screen, characterized in that, include: The subpixel brightness map acquisition unit is used to acquire the subpixel brightness maps of the screen to be compensated in different pixel channels. The compensation effect map generation unit is used to generate a compensation effect map based on the sub-pixel brightness map. The color space conversion unit is used to perform color space conversion on the compensation effect image to generate a compensation effect image in an opposing color space. The spectrum image generation unit is used to filter the compensation effect map in the opposing color space using a contrast sensitivity function to generate spectrum images for each pixel channel. The human visual segmentation processing unit is used to perform human visual segmentation processing on the spectral image of each pixel channel to generate several fan-shaped segmentation regions. The color moiré quantization index generation unit is used to generate the color moiré quantization index of the compensation effect map based on the pixel contrast and orientation factor of the plurality of sector segmentation regions.

9. The quantization device according to claim 8, characterized in that, The color moiré quantization index generation unit specifically includes: The contrast threshold and weight parameters for different color channels are obtained based on the display characteristics of the screen to be compensated. The color moiré quantization index of the compensation effect map is generated based on the contrast threshold, the weight parameters of different color channels, the pixel contrast of the several sector segmentation regions, and the orientation factor.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains a program that, when executed on a computer, performs the quantization method as described in any one of claims 1 to 7.

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