Parameterless Discrete Regularization on Graphs for Color Image Filtering

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.

• Type: Conference
• Year: 2007
• Where: ICIAR
• Authors: Olivier Lezoray, Sébastien Bougleux, Abderrahim Elmoataz
• Keywords: Discrete Regularization, Discrete Regularization Framework, General Discrete Regularization, ICIAR 2007