Discrete Regularization on Weighted Graphs for Image and Mesh FilteringReport as inadecuate




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* Corresponding author 1 Equipe Image - Laboratoire GREYC - UMR6072 GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen 2 LMIA - Laboratoire de Mathématiques Informatique et Applications

Abstract : We propose a discrete regularization framework on weighted graphs of arbitrary topology, which unifies image and mesh filtering. The approach considers the problem as a variational one, which consists in minimizing a weighted sum of two energy terms: a regularization one that uses the discrete p-Laplace operator, and an approximation one. This formulation leads to a family of simple nonlinear filters, parameterized by the degree p of smoothness and by the graph weight function. Some of these filters provide a graph-based version of well-known filters used in image and mesh processing, such as the bilateral filter, the TV digital filter or the nonlocal mean filter.





Author: Sébastien Bougleux - Abderrahim Elmoataz - Mahmoud Melkemi -

Source: https://hal.archives-ouvertes.fr/



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