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A low-rank denoising method and device based on self-similarity of real color images

A self-similar, color image technology, applied in the field of image processing, can solve the problems of different degrees of similarity of similar blocks, incomplete removal of noise in smooth areas, loss of information in texture areas, etc., and achieve the effect of high speed.

Active Publication Date: 2022-07-05
FUZHOU UNIV
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Problems solved by technology

However, in natural images, the similarity of similar blocks varies, so the effect of denoising is often that the noise in the smooth area is not completely removed, and the texture area has begun to lose information. This has always been a problem in low-rank denoising.

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  • A low-rank denoising method and device based on self-similarity of real color images
  • A low-rank denoising method and device based on self-similarity of real color images
  • A low-rank denoising method and device based on self-similarity of real color images

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Embodiment Construction

[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0042] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0043] It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates that There are features, steps, operations, devices, compone...

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Abstract

The invention relates to a low-rank denoising method and device based on the self-similarity of real color images. First, the image is divided into blocks, then the image blocks are clustered, and the clustered similar block groups are subjected to an average Mahalanobis distance calculation. Calculation; according to the average Mahalanobis distance, the image is divided into smooth area, simple texture area and complex texture area; finally, the blocks of smooth area, simple texture area and complex texture area are respectively denoised for different times, and the denoised image is obtained. image. The present invention can improve the overall effect of image denoising.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a low-rank denoising method and device based on the self-similarity of real color images. Background technique [0002] The non-local average denoising algorithm takes advantage of the characteristic of the ubiquitous redundant information in the image, finds similar blocks globally and takes the average to remove noise. A new era of noise. ShuhangGu, LeiZhang and others later proposed the WNNM method. By dividing the image into small image blocks, and then looking for similar blocks in the neighborhood of the image blocks to form similar block groups, using the low rank of the similar block groups of pure images, the similar blocks The group performs singular value decomposition, and then removes the small singular values ​​in the singular value matrix to achieve the effect of denoising. However, in natural images, similar blocks have different degrees of similarity, ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10004G06T2207/10024G06T2207/20021
Inventor 陈飞杨晨
Owner FUZHOU UNIV
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