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Semi-Split Bregman Iteration Algorithm for Image Denoising
Zhang Jun 1 * #,Wei Zhihui 2
1.School of Sicence, Nanjing university of Science and Technology
2.School of Computer Science and Technology,Nanjing University of Science and Technology
*Correspondence author
#Submitted by
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Funding: National Natural Science Foundation of China （No.No.60802039 and 61071146）, This work was supported by the Specialized Research Fund for the Doctoral Program of Higher Education （No.No.200802880018）, NJUST Research Funding （No.No.2010ZYT070)）
Opened online:31 December 2010
Accepted by: none
Citation: Zhang Jun,Wei Zhihui.Semi-Split Bregman Iteration Algorithm for Image Denoising[OL]. [31 December 2010] http://en.paper.edu.cn/en_releasepaper/content/4401265
 
 
The split Bregman iteration has been demonstrated to be an efficient tool for solving total variation regularized minimization problems. In denosing case, it can remove noise efficiently, but it can not preserve textures well. In this paper, we analyze the split Bregman method from the perspective of function matching, and reveal the reason why it can not preserve textures well. Based on this analysis, we develop a new method called the semi-split Bregman iteration algorithm for image denoising. The numerical results show that the semi-split Bregman iteration algorithm can preserve the textures and improve the peak signal to noise ratio efficiently in the processing of denoising.
Keywords:image denoising; texture preserving; split Bregman iteration
 
 
 

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