A Cooperative Denoising Method Based on Total Variation and Discrete Wavelet Transform

被引：0

作者：

Xie, Lei ^{[1
]}

Wu, Tao ^{[1
]}

Chen, Xi ^{[2
]}

He, Jia ^{[1
]}

机构：

[1] Chengdu Univ Informat Technol, Dept Comp Sci, Chengdu, Sichuan, Peoples R China

[2] Southwest Minzu Univ, Sch Comp Sci & Technol, Chengdu, Sichuan, Peoples R China

来源：

PROCEEDINGS OF THE 2018 IEEE 22ND INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN ((CSCWD)) | 2018年

关键词：

Image Denoising; Total variation; Discrete Wavelet Transform; Hybrid Model; PARTICLE SWARM OPTIMIZATION;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The traditional total variation denoising method is prone to spurious edges under high noise conditions. This paper proposed a cooperative filtering method, which combines discrete wavelet transform (DWT) and total variation (TV). The total variation method is used to obtain the denoised image, and then the discrete wavelet transform is performed. The denoised image undergoes wavelet decomposition and reconstruction, could reduce the edge effect and improve the image quality. The experimental results show that the proposed method could solve the noise suppression of variational problems, at the same time, it could provide better peak signal to noise ratio and some other parameters.

引用

页码：45 / 49

页数：5

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