# $\Gamma$-convergence of discrete functionals with nonconvex perturbation for image classification

created by march on 20 Dec 2004

[BibTeX]

Published Paper

Inserted: 20 dec 2004

Journal: SIAM J. Numer. Anal.
Volume: 42
Number: 3
Pages: 1128-1145
Year: 2004

Abstract:

The purpose of this paper is to show the theoretical soundness of a variational method proposed in image processing for supervised classification. Based on works developed for phase transitions in fluid mechanics, the classification is obtained by minimizing a sequence of functionals. The method provides an image composed of homogeneous regions with regular boundaries, a region being defined as a set of pixels belonging to the same class. In this paper, we show the Gamma-convergence of the sequence of functionals which differ from the ones proposed in fluid mechanics in the sense that the perturbation term is not quadratic but has a finite asymptote at infinity, corresponding to an edge preserving regularization term in image processing.

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