文章基本信息

标题：Image Denoising via Robust Simultaneous Sparse Coding
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作者：Li, Lei ; Kan, Jiangming ; Li, Wenbin 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2014
卷号：9
期号：6
页码：1418-1425
DOI：10.4304/jcp.9.6.1418-1425
语种：English
出版社：Academy Publisher
摘要：Simultaneous sparse coding (SSC) has shown great potential in image denoising, because it exploits dependencies of patches in nature images. However, imposing joint sparsity might neglect the sight difference between patches. In this paper, we propose an image denoising algorithm based on robust simultaneous sparse coding (RSSC). In our algorithm, the sparse coefficient matrix is decomposed into two parts. One coefficient matrix is imposed on the joint sparse regularizer which exploits self-similarities of image patches while the other matrix is imposed by the elementwise sparse regularizer which considers the subtle differences between patches. Experiments on the benchmark data show the superior performance over the state-of-art algorithms.
关键词：Image denoising;robust simultaneous sparse coding;regularization;accelerated proximal gradient (APG)