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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Lezoray, O., Bougleux, S., & Elmoataz, A. (2007). Parameterless discrete regularization on graphs for color image filtering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4633 LNCS, pp. 46–57). Springer Verlag. https://doi.org/10.1007/978-3-540-74260-9_5
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