DocumentCode :
1501454
Title :
On the Total Variation Dictionary Model
Author :
Zeng, Tieyong ; Ng, Michael K.
Author_Institution :
Institute for Computational Mathematics, Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong
Volume :
19
Issue :
3
fYear :
2010
fDate :
3/1/2010 12:00:00 AM
Firstpage :
821
Lastpage :
825
Abstract :
The goal of this paper is to provide a theoretical study of a total variation (TV) dictionary model. Based on the properties of convex analysis and bounded variation functions, the existence of solutions of the TV dictionary model is proved. We then show that the dual form of the model can be given by the minimization of the sum of the l^1 -norm of the dual solution and the Bregman distance between the curvature of the primal solution and the subdifferential of TV norm of the dual solution. This theoretical result suggests that the dictionary must represent sparsely the curvatures of solution image in order to obtain a better denoising performance.
Keywords :
Curvature; dictionary; dual problem; sparse representation; total variation;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2009.2034701
Filename :
5288597
Link To Document :
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