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Transform domain/joint sparse representation-based image reconstruction method

A technology of joint sparseness and image reconstruction, which is applied in image enhancement, image analysis, image data processing, etc., to achieve the effect of improving performance

Inactive Publication Date: 2017-10-27
CHONGQING UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to propose an image reconstruction method based on the joint sparse representation of the transform domain in view of the shortcomings of the existing image reconstruction methods for sparse coefficient constraints

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  • Transform domain/joint sparse representation-based image reconstruction method
  • Transform domain/joint sparse representation-based image reconstruction method
  • Transform domain/joint sparse representation-based image reconstruction method

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Embodiment Construction

[0025] refer to figure 1 , the present invention is an image reconstruction method based on transform domain joint sparse representation, and the specific steps include the following:

[0026] Step 1. Obtain a set of similar image blocks by comparing the similarity with the target image block.

[0027] (1a) Input an image to be reconstructed, and size the image Extract image blocks pixel by pixel to obtain all image blocks;

[0028] (1b) For image block x at position i i , within the search radius S, the similarity comparison is performed by comparing the Euclidean distance, and the similarity values ​​are sorted;

[0029] (1c) Take out the L-1 image blocks with the highest similarity value with the target image block, and form a set of similar image blocks with the target image block

[0030] In step 2, a collection of similar image blocks is sparsely represented in the transform domain.

[0031] (2a) put x i Corresponding set of similar image blocks Stack similar ...

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Abstract

The invention discloses a transform domain joint sparse representation-based image reconstruction method, and belongs to the technical field of digital image processing. The image reconstruction method combines transform domain sparse representation and joint sparse representation. The method comprises the following steps of: searching a similar image block set through similar image block matching; carrying out wavelet transform and discrete cosine transform on the similar image block set at a transform domain so as to obtain sparse coefficients; respectively solving non-local estimated values and joint constraint parameters of the sparse coefficients through non-local weighted average and Bayesian estimation with a maximum posterior probability; and finally efficiently solving a sparse model by utilizing a Bergman iteration algorithm so as to obtain a final estimation result. According to the method, joint sparse constraint is carried out on the sparse coefficients at the transform domain, so that the lost information of real images can be restored more effectively while the obtained images can retain more details, the overall effects of the images are closer to the real images, and the method can be used for image restoration and de-blurring.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a method for reconstructing an image by sparsely expressing the image in a transformation domain, which is used for optical image restoration and deblurring processing. Background technique [0002] Image reconstruction has always been a hot research direction in image processing, and is widely used in image denoising, image restoration and image deblurring. With the development of compressed sensing technology in recent years, sparse representation has become an important technique for image reconstruction. [0003] In order to obtain more sparse coefficients, the traditional sparse representation method processes the dictionary used in sparse representation, from commonly used fixed dictionaries (such as discrete cosine dictionaries, wavelet dictionaries, etc.) adaptability. Then the non-local similarity of the image is gradually used, and has a v...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/10G06K9/62
CPCG06T5/10G06T2207/20021G06T2207/20048G06F18/22G06T5/00G06T5/73G06T5/70
Inventor 刘书君沈晓东曹建鑫杨婷唐明春周喜川
Owner CHONGQING UNIV
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