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
fDate :
3/1/2010 12:00:00 AM
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
-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;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2009.2034701