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An Image Denoising Method Based on Adaptive Weighted Total Variation

An adaptive weighting, total variation technique, applied in the field of image processing

Active Publication Date: 2020-04-17
THE 28TH RES INST OF CHINA ELECTRONICS TECH GROUP CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method has exactly the same total variation weighting parameters in different directions of the image, and cannot set specific total variation weighting parameters for images with different information in different directions.

Method used

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  • An Image Denoising Method Based on Adaptive Weighted Total Variation
  • An Image Denoising Method Based on Adaptive Weighted Total Variation
  • An Image Denoising Method Based on Adaptive Weighted Total Variation

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Experimental program
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Embodiment

[0126] In the following experiments, peak signal to noise ratio (Peak signal to noise ratio, PSNR) is used to denoise the total variation image denoising method and the image denoising method based on an adaptive weighted total variation image denoising method proposed by the present invention ability to compare.

[0127] The mathematical definition of peak signal-to-noise ratio is:

[0128]

[0129] In the formula (16), the size of the image is M×N, the range of the gray value is L, x represents the original image, and y represents the detected image.

[0130] The peak signal-to-noise ratio represents the degree of difference between the original image and the detected image. The larger the value of the peak signal-to-noise ratio, the smaller the difference between the original image and the detected image, and the more realistic it is.

[0131] Normalize the original "Lena", "Barbara", "Cameraman", and "Moon", and add Gaussian white noise with a normal distribution mean ...

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PUM

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Abstract

The invention discloses an image denoising method based on self-adaptive weighted total variation. The method includes the following steps: step 1, establishing a weighted-total-variation image denoising model; step 2, normalizing an image; step 3, constructing a matrix pair of (u, v), and carrying out initial value assignment thereon; step 4, starting a k-th iteration, and generating values of weighting parameters of W<1><k> and W<2><k> in a self-adaptive manner according to values of a matrix pair of (u<k-1>, v<k-1>); step 5, obtaining a denoised image of x<k> of the k-th iteration; and step6, judging whether an iteration number of k reaches a set iteration number of N, if the iteration number of k does not reach the set iteration number of N, utilizing a gradient projection algorithm to obtain a matrix pair of (u<k>, v<k>), letting k = k + 1, and re-entering the step 4, and obtaining a final denoised image of x<N> if the iteration number of k reaches the set iteration number of N.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image denoising method based on adaptive weighted total variation. Background technique [0002] Images contain extremely rich information, and are the most direct and effective channels for human beings to obtain information. However, in the process of image acquisition, transmission, and storage, a certain degree of noise is bound to be mixed in, which not only reduces the quality of the image, but also brings difficulties to the subsequent analysis and processing of the image. Therefore, image denoising is a very important and indispensable link in the field of image processing. [0003] Among many image denoising algorithms, the total variation algorithm can effectively protect image edge information while removing image noise, and has achieved good results in image denoising, so it has been widely used. Beck et al. applied the gradient projection algorithm to t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002
Inventor 廖帆孙亭满青珊贲伟安振宇李方婷张晖吴丹清
Owner THE 28TH RES INST OF CHINA ELECTRONICS TECH GROUP CORP