Image Restoration with Dual-Prior Constraint Models Based on Split Bregman

Li AO; Li YIBING; Yang XIAODONGLiu YUE

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Image Restoration with Dual-Prior Constraint Models Based on Split Bregman

机译：Image Restoration with Dual-Prior Constraint Models Based on Split Bregman

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摘要

In order to utilizing the local and non-local information in the image, we proposed a novel sparse scheme for image restoration in this paper. The new scheme includes two important contributions. The first one is that we extended the image prior model in conventional total variation to the dual-prior models for combining the local smoothness and nonlocal sparsity under regularization framework. The second one is we developed a modified iterative Split Bregman majorization method to solve the objective function with dual-prior models. The experimental results show that the proposed scheme achieved the state-of-the-art performance compared to the current restoration algorithms.

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来源
《Optical review》 |2013年第6期|491-495|共5页
作者
Li AO; Li YIBING; Yang XIAODONGLiu YUE;
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作者单位

Institute of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;

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原文格式 PDF
正文语种英语
中图分类光学;
关键词
image restoration; non-local sparsity; Split Bregman; total variation; regularization;

Image Restoration with Dual-Prior Constraint Models Based on Split Bregman

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