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An Adaptive Block Compressive Sensing Image Reconstruction Method

A block compressed sensing and image reconstruction technology, applied in image enhancement, image analysis, image data processing, etc., to achieve the effect of improving reconstruction accuracy, robustness, and accuracy

Active Publication Date: 2021-11-05
HENGYANG NORMAL UNIV
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  • Application Information

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide an image reconstruction method based on adaptive block compression sensing to solve the block effect existing in block reconstruction in existing block compression sensing image reconstruction. problems, improve the accuracy of reconstruction

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  • An Adaptive Block Compressive Sensing Image Reconstruction Method
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Embodiment approach

[0061] Step 1, for the image s, first perform the size adjustment operation, and normalize the image with a size of 256*256, so that s∈R 256 ×256 , and N=256=2 8 Take K1=8+1=9.

[0062] Step 2: Segment the adjusted image in a variety of ways. There are K1=9 ways to divide the blocks, in which the sizes of 9 blocks are defined, which are respectively w 1 × h 1 (1×256), w 2 × h 2 (2×128),w 3 × h 3 (4×64),

[0063] w 4 × h 4 (8×32), w 5 × h 5 (16×16), w 6 × h 6 (32×8), w 7 × h 7 (64×4), w 8 × h 8 (128×2),w 9 × h 9 (256×1).

[0064] Step 3, segment the image s, and define the segmented result as Set the iteration parameter k1=0 for iterative calculation of different block methods,

[0065] Step 4, using w k1 × h k1 Segment the s image to get a total of 256 sub-blocks, and each sub-block is marked as s (1) ,s (2) ,...,s (256) , set the iteration parameter k2=1, a total of 256 iterations, and iteratively calculate sub-blocks.

[0066] Step 5, put s (k2)...

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Abstract

The invention discloses an image reconstruction method based on self-adaptive block compression perception. By adopting different block methods, the image is divided into blocks in various forms, and then the method of minimizing the second normal form is used for the block results respectively. Perform compression reconstruction. By comparing the sparsity of the reconstruction results of each block method, the reconstruction result with the largest sparseness is adaptively selected, and finally the optimal result is obtained through inverse transformation. The method of the invention has strong robustness, solves the problem of block effect existing in block reconstruction in existing block compressed sensing image reconstruction, and improves the reconstruction effect.

Description

technical field [0001] The invention relates to a block compression sensing image reconstruction method, in particular to an adaptive block compression sensing image reconstruction method. Background technique [0002] Compressed Sensing (CS) is an emerging theoretical system that has received extensive attention in the field of image processing in recent years. According to the compressed sensing theory, if an image to be sampled is sparse (or sparse in a transform domain), then the original image can be accurately restored with high probability from its limited uncorrelated measurement values. In 2006, scholars such as Candes, Donoho, and Tao proved mathematically that signals can be accurately reconstructed from some Fourier transform coefficients. Compressed sensing theory points out that the compressible signal can be measured in a way far below the Nyquist standard, and the original signal can still be accurately restored. After a picture or signal undergoes some kin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T7/11G06T7/136
CPCG06T7/11G06T7/136G06T2207/20004G06T5/00
Inventor 赵辉煌郑金华邹祎孙雅琪
Owner HENGYANG NORMAL UNIV