• 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