A Parallel Proximal Splitting Method for Disparity Estimation from Multicomponent Images Under Illumination Variation

Authors:
C. Chaux;M. El-Gheche;J. Farah;J. -C. Pesquet;B. Pesquet-Popescu
Affiliations:
Laboratoire d'Informatique Gaspard Monge--CNRS UMR 8049, Université Paris-Est, Marne la Vallée Cedex 2, France 77454;Laboratoire d'Informatique Gaspard Monge--CNRS UMR 8049, Université Paris-Est, Marne la Vallée Cedex 2, France 77454;Department of Telecommunications, Faculty of Engineering, Holy-Spirit University of Kaslik, Jounieh, Lebanon;Laboratoire d'Informatique Gaspard Monge--CNRS UMR 8049, Université Paris-Est, Marne la Vallée Cedex 2, France 77454;Signal and Image Proc. Dept., Telecom ParisTech, Paris, France 75014
Venue:
Journal of Mathematical Imaging and Vision
Year:
2013

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Abstract

Proximal splitting algorithms play a central role in finding the numerical solution of convex optimization problems. This paper addresses the problem of stereo matching of multi-component images by jointly estimating the disparity and the illumination variation. The global formulation being non-convex, the problem is addressed by solving a sequence of convex relaxations. Each convex relaxation is non trivial and involves many constraints aiming at imposing some regularity on the solution. Experiments demonstrate that the method is efficient and provides better results compared with other approaches.