Parameterless discrete regularization on graphs for color image filtering

  • Authors:
  • Olivier Lezoray;Sébastien Bougleux;Abderrahim Elmoataz

  • Affiliations:
  • Université de Caen, LUSAC EA 2607, Saint-Lô, France;ENSICAEN, GREYC, Caen, France;Université de Caen, LUSAC EA 2607, Saint-Lô, France

  • Venue:
  • ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
  • Year:
  • 2007

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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.