CN108830909B - Image preprocessing system and method for improving compression ratio of periodic texture image - Google Patents

Image preprocessing system and method for improving compression ratio of periodic texture image Download PDF

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CN108830909B
CN108830909B CN201810509572.0A CN201810509572A CN108830909B CN 108830909 B CN108830909 B CN 108830909B CN 201810509572 A CN201810509572 A CN 201810509572A CN 108830909 B CN108830909 B CN 108830909B
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梅林海
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Wuhan Jingce Electronic Group Co Ltd
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Abstract

The invention relates to an image preprocessing system for improving the compression ratio of a periodic texture image.A sampling module of the image preprocessing system forms pixels with the same phase in each texture period in a defect detection image of a display panel containing periodic texture into a sampling image, and extracts a plurality of sampling images corresponding to all the pixels with different phases in each texture period in the defect detection image of the display panel; the grid arrangement module carries out grid arrangement on the plurality of sampling images according to the self phase position of each sampling image to form a reconstructed image with the resolution equal to that of the defect detection image of the display panel; and the image compression module performs lossy compression or lossless compression on the reconstructed image to obtain code stream data. The invention has higher image compression ratio and can facilitate the storage and transmission of texture images.

Description

Image preprocessing system and method for improving compression ratio of periodic texture image
Technical Field
The invention relates to the technical field of image processing, in particular to an image preprocessing system and method for improving the compression ratio of a periodic texture image.
Technical Field
In the process of automatic optical detection of a TFT (Thin Film Transistor) array of a liquid crystal panel, 10 to 30 lossless digital images with a resolution of 6576 × 4384 or 10000 × 7096 are required to be taken, in the optical detection process, a planar array camera is generally used for taking the lossless digital images, and then JPEG-LS (Joint Photographic Experts Group-lossless) is used for lossless compression to compress the taken lossless digital images for transmission and storage.
Disclosure of Invention
The invention aims to provide an image preprocessing system and method for improving the compression ratio of a periodic texture image, wherein the system and method have higher image compression ratio and can facilitate the storage and transmission of the texture image.
To achieve the object, the present invention provides an image preprocessing system for improving the compression ratio of a periodic texture image, which is characterized in that: the method comprises an image sampling module, a grid arrangement module and an image compression module, wherein the image sampling module is used for forming pixels with the same phase in each texture period in a display panel defect detection image containing periodic textures into a sampling image, and extracting a plurality of sampling images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
the grid arrangement module is used for carrying out grid arrangement on the plurality of sampling images according to the self phase position of each sampling image to form a reconstructed image with the resolution equal to that of the defect detection image of the display panel;
and the image compression module is used for carrying out lossy compression or lossless compression on the reconstructed image to obtain code stream data.
A decompression system corresponding to the image preprocessing system comprises a data acquisition module, a decompression module, a resolution calculation module, an image blocking module and an image restoration module; the data acquisition module is used for acquiring the code stream data and image texture parameters and image resolution parameters in the reconstructed image;
the decompression module is used for carrying out lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
the resolution calculation module is used for calculating the resolution of the sampled image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image;
the image blocking module is used for blocking the pre-decompressed image by taking the resolution of the sampled image of each phase as the resolution of the image block to obtain a plurality of sampled images;
the image restoration module is used for sequentially arranging the pixel values of the plurality of sampling images according to the phase sequence of the phase of each sampling image in the periodic texture of the defect detection image of the display panel to obtain a final decompressed image.
An image preprocessing method for improving the compression ratio of a periodic texture image comprises the following steps:
step 1: the image sampling module combines pixels with the same phase in each texture period in a display panel defect detection image containing periodic textures into a sampling image, and extracts a plurality of sampling images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
step 2: the grid arrangement module carries out grid arrangement on the plurality of sampling images according to the phase position of each sampling image to form a reconstructed image with the same resolution as the display panel defect detection image;
and 3, step 3: and the image compression module performs lossy compression or lossless compression on the reconstructed image to obtain code stream data.
A decompression method of the image preprocessing method comprises the following steps:
step 01: a data acquisition module acquires the code stream data and image texture parameters and image resolution parameters in a reconstructed image;
step 02: the decompression module carries out lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
the resolution calculation module calculates the resolution of the sampled image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image;
step 03: the image blocking module blocks the pre-decompressed image by taking the resolution of the sampled image of each phase as the resolution of the image block to obtain a plurality of sampled images;
step 04: and the image restoration module is used for sequentially arranging the pixel values of the plurality of sampling images according to the phase sequence of the periodic texture of the phase of each sampling image in the defect detection image of the display panel to obtain a final decompressed image.
The system and the method adopt a two-dimensional image homography coordinate transformation mode which is reversible, and texture decomposition is carried out in the two-dimensional image homography coordinate transformation mode, so that high-frequency response in a strong periodic texture image frequency spectrum can be obviously reduced, namely, the image becomes smooth and is easier to compress.
In addition, the invention also designs a decompression system and a decompression method which are opposite to the image preprocessing method, and the decompression system and the decompression method adopt the inverse transformation of the homography coordinate of the two-dimensional image to accurately decompress the compressed file so as to obtain an accurate display panel defect detection image containing the periodic texture.
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FIG. 1 is a schematic diagram of an image preprocessing system according to the present invention;
FIG. 2 is a schematic diagram of the decompression system of the present invention;
the system comprises an image sampling module, a grid arrangement module 2, an image compression module 3, a data acquisition and output module 4, a data acquisition module 5, a data decompression module 6, a resolution calculation module 7, an image blocking module 8 and an image restoration module 9.
Detailed Description
The invention is described in further detail below with reference to the following figures and specific examples:
the invention is suitable for carrying on the texture periodic image that the automatic optical detection process shoots to the TFT array of the liquid crystal panel and compressing the backup link, the image preprocessing system of the periodic texture image compression ratio of promotion that the invention designs, it includes the image sampling module 1, the grid arranges the module 2, the image compression module 3 and data acquisition output module 4, wherein, the data output end of the image sampling module 1 connects the data input end of the grid arranges the module 2, the data output end of the grid arranges the module 2 and connects the data input end of the image compression module 3, the data output end of the image compression module 3 connects the data input end of the data acquisition output module 4, the data output end of the data acquisition output module 4 is used for connecting the memorizer or data transmission network;
the image sampling module 1 is configured to combine pixels with the same phase in each texture period in a display panel defect detection image with periodic texture into one sampled image, and extract a plurality of sampled images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
the grid arrangement module 2 is used for carrying out grid arrangement on the plurality of sampling images according to the self phase position of each sampling image to form a reconstructed image with the resolution equal to that of the defect detection image of the display panel;
and the image compression module 3 is used for carrying out lossy compression or lossless compression on the reconstructed image to obtain code stream data.
And the data acquisition output module 4 is used for acquiring and outputting the code stream data and the image texture parameters and the image resolution parameters in the reconstructed image.
The horizontal period and the vertical period of the periodic texture contained in the display panel defect detection image are between 3 and 20 pixels, and the texture has larger contrast, namely the difference between the brightest pixel value and the darkest pixel value is larger than 30.
In the above technical solution, the lossy compression includes jpeg lossy image coding compression and jpeg2000 lossy image coding compression.
In the above technical solution, the lossless compression includes lossless compression of images based on static and dynamic huffman coding algorithms, lossless compression of images based on arithmetic coding algorithms (JPEG-LS lossless compression), lossless compression of images based on LZW (string table compression algorithm) coding and its improved algorithm, lossless compression of images based on run-length coding and improved adaptive run-length coding algorithm, lossless compression of images based on feinunn coding algorithm, and lossless compression of JPEG2000 lossless image coding.
A decompression system corresponding to the system comprises a data acquisition module 5, a decompression module 6, a resolution calculation module 7, an image blocking module 8 and an image restoration module 9, wherein the data output end of the data acquisition module 5 is connected with the data input end of the decompression module 6, the data output end of the decompression module 6 is connected with the data input end of the resolution calculation module 7, the data output end of the resolution calculation module 7 is connected with the data input end of the image blocking module 8, and the data output end of the image blocking module 8 is connected with the data input end of the image restoration module 9;
the data acquisition module 5 is used for acquiring the code stream data and image texture parameters and image resolution parameters in the reconstructed image;
the decompression module 6 is used for carrying out lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
the resolution calculation module 7 is used for calculating the resolution of the sampled image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image;
the image blocking module 8 is configured to block the pre-decompressed image to obtain a plurality of sampled images by using the resolution of the sampled image of each phase as the resolution of the image block;
the image restoration module 9 is configured to sequentially arrange the pixel values of the multiple sampling images according to the phase sequence of the periodic texture of the phase of each sampling image in the defect detection image of the display panel to obtain a final decompressed image.
In the above technical solution, the lossy decompression includes jpeg lossy image codec decompression and jpeg2000 lossy image codec decompression.
The lossless decompression comprises lossless decompression of images based on static and dynamic Huffman coding algorithms, lossless decompression of images based on arithmetic coding algorithms, lossless decompression of images based on LZW coding and improved algorithms thereof, lossless decompression of images based on run length coding and improved adaptive run length coding algorithms, lossless decompression of images based on Voronoi Shannon coding algorithms and lossless decompression of jpeg2000 lossless image coding.
An image preprocessing method for improving the compression ratio of a periodic texture image is characterized by comprising the following steps of:
step 1: the image sampling module 1 combines pixels with the same phase in each texture period in a display panel defect detection image containing periodic textures into a sampling image, and extracts a plurality of sampling images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
step 2: the grid arrangement module 2 is used for carrying out grid arrangement on the plurality of sampling images according to the self phase position of each sampling image to form a reconstructed image with the resolution equal to that of the defect detection image of the display panel;
and step 3: and the image compression module 3 performs lossy compression or lossless compression on the reconstructed image to obtain code stream data.
And the data acquisition and output module 4 acquires and outputs the code stream data and the image texture parameters and the image resolution parameters in the reconstructed image.
In step 1 of the above technical solution, a display panel defect detection image including a periodic texture is represented as I (x, y), where a horizontal coordinate x of the defect detection image is 0,1,2, … …, W-1; the vertical coordinate y of the defect detection image is 0,1,2, … …, H-1; w is the horizontal resolution of the image, H is the vertical resolution of the image;
a plurality of sampling images corresponding to all the pixels with different phases in each texture period in the defect detection image of the display panel are represented as D i,j (x1, y1) ═ I (x1 × N + I, y1 × M + j) where the sampled image horizontal coordinates x1 are 0,1,2, … …, a-1; the sampled image vertical coordinate y1 is 0,1,2, … …, B-1, where N is the texture horizontal period, M is the texture vertical period, the horizontal direction texture number a is W/N, the vertical direction texture number B is H/M, the horizontal phase i is 0,1,2, … …, N-1; vertical phase j is 0,1,2, … …, M-1; the unit is a pixel;
Figure BDA0001671865150000061
in step 2, the reconstructed image F is represented by the matrix D i,j Form a composition
Figure BDA0001671865150000062
A decompression method of the above method, comprising the steps of:
step 01: the data acquisition module 5 acquires the code stream data and image texture parameters and image resolution parameters in the reconstructed image;
step 02: the decompression module 6 performs lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
the resolution calculation module 7 calculates the resolution of the sampled image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image (assuming that the horizontal resolution is W, the vertical resolution is H, the horizontal period of the texture is N, and the vertical period is M, the number of horizontal textures a is W/N, the number of vertical textures B is H/M, and the number of texture periods is equivalent to the resolution of the sampled image of each phase);
step 03: the image blocking module 8 blocks the pre-decompressed image by using the resolution of the sampled image of each phase as the resolution of the image block to obtain a plurality of sampled images;
step 04: the image restoration module 9 sequentially arranges the pixel values of the plurality of sample images according to the phase sequence of the periodic texture of the phase of each sample image in the defect detection image of the display panel to obtain a final decompressed image.
In the above step 02, the pre-decompressed image I1(x2, y2) has horizontal coordinates x2 of 0,1,2, … …, W1-1; the vertical coordinate y2 of the pre-decompressed image is 0,1,2, … …, H1-1, W1 is the horizontal resolution of the pre-decompressed image, and H1 is the vertical resolution of the pre-decompressed image;
multiple sampled images E i,j (x3, y3) ═ I1(I1 a1+ x3, j 1B 1+ y3), in which the sample image horizontal coordinates x3 are 0,1,2, … …, a 1-1; the sampled image vertical coordinate y3 is 0,1,2, … …, B1-1; the sampling image horizontal phase i1 is 0,1,2, … …, N1-1; the sampled image vertical phase j1 is 0,1,2, … …, M1-1; the number of textures in the horizontal direction of the sampled image A1 is W1/N1, and the number of textures in the vertical direction of the sampled imageThe number B1 is H1/M1.
Figure BDA0001671865150000071
The decompressed image F1 is composed of a plurality of sample images E i,j (x3, y3) are alternately arranged according to their phases to obtain:
Figure BDA0001671865150000072
details not described in this specification are within the skill of the art that are well known to those skilled in the art.

Claims (10)

1. An image preprocessing system for improving the compression ratio of periodic texture images is characterized in that: the method comprises an image sampling module (1), a grid arrangement module (2) and an image compression module (3), wherein the image sampling module (1) is used for enabling pixels with the same phase in each texture period in a display panel defect detection image containing periodic textures to form a sampling image, and extracting a plurality of sampling images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
the grid arrangement module (2) is used for carrying out grid arrangement on the plurality of sampling images according to the phase position of each sampling image to form a reconstructed image with the same resolution as the display panel defect detection image;
the image compression module (3) is used for carrying out lossy compression or lossless compression on the reconstructed image to obtain code stream data;
multiple sampling images corresponding to all pixels with different phases in each texture period in the defect detection image of the display panel are represented as a matrix D i,j (x1, y1) ═ I (x1 × N + I, y1 × M + j) where the sampled image horizontal coordinates x1 are 0,1,2, … …, a-1; the vertical coordinate y1 of the sampled image is 0,1,2, … …, B-1, N is the horizontal period of texture, M is the vertical period of texture, the number a of textures in the horizontal direction is W/N, the number B of textures in the vertical direction is H/M, and the horizontal phase i is H0,1,2, … …, N-1; vertical phase j is 0,1,2, … …, M-1; w is the horizontal resolution of the image, and H is the vertical resolution of the image;
decompressing an image from a plurality of sampled images D i,j And the phases are alternately arranged.
2. The image pre-processing system for improving the compression ratio of the periodic texture image according to claim 1, wherein: the device also comprises a data acquisition and output module (4), wherein the data acquisition and output module (4) is used for acquiring and outputting the code stream data and image texture parameters and image resolution parameters in the reconstructed image.
3. The image pre-processing system for improving the compression ratio of the periodic texture image according to claim 1, wherein: the lossy compression includes jpeg lossy image encoding compression and jpeg2000 lossy image encoding compression.
4. The image pre-processing system for improving the compression ratio of the periodic texture image according to claim 1, wherein: the lossless compression comprises lossless compression of images based on static and dynamic Huffman coding algorithms, lossless compression of images based on arithmetic coding algorithms, lossless compression of images based on LZW coding and improved algorithms thereof, lossless compression of images based on run length coding and improved adaptive run length coding algorithms, lossless compression of images based on Voronoi Shannon coding algorithms and lossless compression of jpeg2000 lossless images.
5. A decompression system corresponding to the system of claim 2, characterized in that it comprises a data acquisition module (5), a decompression module (6), a resolution calculation module (7), an image blocking module (8) and an image restoration module (9); the data acquisition module (5) is used for acquiring the code stream data and image texture parameters and image resolution parameters in a reconstructed image;
the decompression module (6) is used for carrying out lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
the resolution calculation module (7) is used for calculating the resolution of the sampling image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image;
the image blocking module (8) is used for blocking the pre-decompressed image by taking the resolution of the sampled image of each phase as the resolution of the image block to obtain a plurality of sampled images;
the image restoration module (9) is used for sequentially arranging the pixel values of the plurality of sampling images according to the phase sequence of the periodic texture of the phase of each sampling image in the defect detection image of the display panel to obtain a final decompressed image.
6. The decompression system according to claim 5, wherein: the lossy decompression comprises jpeg lossy image coding decompression and jpeg2000 lossy image coding decompression.
7. The decompression system according to claim 5, wherein: the lossless decompression comprises lossless decompression of images based on static and dynamic Huffman coding algorithms, lossless decompression of images based on arithmetic coding algorithms, lossless decompression of images based on LZW coding and improved algorithms thereof, lossless decompression of images based on run length coding and improved adaptive run length coding algorithms, lossless decompression of images based on Voronoi Shannon coding algorithms and lossless decompression of jpeg2000 lossless image coding.
8. An image preprocessing method for improving the compression ratio of periodic texture images based on the system of claim 1, comprising the steps of:
step 1: the image sampling module (1) combines pixels with the same phase in each texture period in a display panel defect detection image containing periodic textures into a sampling image, and extracts a plurality of sampling images corresponding to all pixels with different phases in each texture period in the display panel defect detection image;
step 2: the grid arrangement module (2) performs grid arrangement on the plurality of sampling images according to the phase position of each sampling image to form a reconstructed image with the same resolution as the display panel defect detection image;
and 3, step 3: and the image compression module (3) performs lossy compression or lossless compression on the reconstructed image to obtain code stream data.
9. The image preprocessing method according to claim 8, characterized in that; it also includes step 4: and the data acquisition and output module (4) acquires and outputs the code stream data and the image texture parameters and the image resolution parameters in the reconstructed image.
10. A decompression method according to the method of claim 8, characterized in that it comprises the following steps:
step 01: a data acquisition module (5) acquires the code stream data and image texture parameters and image resolution parameters in the reconstructed image;
step 02: the decompression module (6) performs lossy decompression or lossless decompression corresponding to the lossy compression or lossless compression on the code stream data to obtain a pre-decompressed image;
a resolution calculation module (7) calculates the resolution of the sampling image of each phase by using a parameter initialization method according to the texture parameters and the image resolution parameters in the obtained reconstructed image;
step 03: the image blocking module (8) blocks the pre-decompressed image by taking the resolution of the sampled image of each phase as the resolution of the image block to obtain a plurality of sampled images;
step 04: and the image restoration module (9) sequentially arranges the pixel values of the plurality of sampling images according to the phase sequence of the periodic texture of the phase of each sampling image in the defect detection image of the display panel to obtain a final decompressed image.
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