A Relaxed Split Bregman Iteration for Total Variation Regularized Image Denoising

2012 ◽  
pp. 189-197 ◽  
Author(s):  
Jun Zhang ◽  
Zhi-Hui Wei ◽  
Liang Xiao
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Bregman Iteration ◽  
Split Bregman ◽  
Split Bregman Iteration

Total variation blind deconvolution employing split Bregman iteration

2012 ◽  
Vol 23 (3) ◽  
pp. 409-417 ◽  
Author(s):  
Weihong Li ◽  
Quanli Li ◽  
Weiguo Gong ◽  
Shu Tang
Keyword(s):  
Total Variation ◽  
Blind Deconvolution ◽  
Bregman Iteration ◽  
Split Bregman ◽  
Split Bregman Iteration

Removal of Glass Reflection Using TV-Retinex Model

2014 ◽  
Vol 511-512 ◽  
pp. 475-480
Author(s):  
Ke Fei Cheng ◽  
Dan Ni Li
Keyword(s):  
Total Variation ◽  
Computational Approach ◽  
Total Variation Regularization ◽  
Bregman Iteration ◽  
Split Bregman ◽  
Split Bregman Iteration

The Retinex model is mainly used to removal of unfavorable illumination effects from images. In this paper, the Retinex model combined with the total variation regularization (TV-Retinex) is presented to removal of glass reflection that can be solved by a fast computational approach based on the split Bregman iteration. Experiments demonstrated that the proposed method can effectively reduce this kind of artifact as well as preserve the edge and detailed information.

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