Blind image deconvolution with spatially adaptive total variation regularization

被引：58

作者：

Yan, Luxin ^{[1
]}

Fang, Houzhang ^{[1
]}

Zhong, Sheng ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sci & Technol Multispectral Informat Proc Lab, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Hubei, Peoples R China

来源：

OPTICS LETTERS | 2012年 / 37卷 / 14期

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1364/OL.37.002778

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

A blind deconvolution algorithm with spatially adaptive total variation regularization is introduced. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Comparative results on simulated and real degraded images are reported. (c) 2012 Optical Society of America

引用

页码：2778 / 2780

页数：3

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