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Parameterless Discrete Regularization on Graphs for Color Image Filtering

  • Olivier Lezoray
  • Sébastien Bougleux
  • Abderrahim Elmoataz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4633)

Abstract

A discrete regularization framework on graphs is proposed and studied for color image filtering purposes when images are represented by grid graphs. Image filtering is considered as a variational problem which consists in minimizing an appropriate energy function. In this paper, we propose a general discrete regularization framework defined on weighted graphs which can be seen as a discrete analogue of classical regularization theory. With this formulation, we propose a family of fast and simple anisotropic linear and nonlinear filters. The parameters of the proposed discrete regularization are estimated to have a parameterless filtering.

Keywords

Weight Function Color Image Weighted Graph Impulse Noise Restore Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Olivier Lezoray
    • 1
  • Sébastien Bougleux
    • 2
  • Abderrahim Elmoataz
    • 1
  1. 1.Université de Caen, LUSAC EA 2607, Vision and Image Analysis Team, IUT SRC, 120 Rue de l’exode, Saint-Lô, F-50000France
  2. 2.ENSICAEN, GREYC, 6 Bd. Maréchal Juin, Caen, F-14050France

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