Blurred image restoration method based on second-order total generalized variation regularization

被引：0
|
作者：
Ren, Fu-Quan [1 ]
Qiu, Tian-Shuang [1 ]
机构：
[1] Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2015年 / 41卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Deblurring; Image restoration; Second-order total generalized variation; Split Bregman iteration;
D O I：
10.16383/j.aas.2015.c130616
中图分类号：
学科分类号：
摘要：
For the blurred image restoration problem, we adopt the second-order total generalized variation as the regularization term to construct an image restoration model. For the high order and non-smooth feature of the restoration model, a fast algorithm based on the split Bregman iterative algorithm is also proposed. Experimental results show that the model and the numerical algorithm can effectively restore the images polluted by noise and blur, and they can preserve image texture and details effectively. Copyright © 2015 Acta Automatica Sinica. All rights reserved.
引用
收藏
页码：1166 / 1172
页数：6
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