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Journal Articles Journal of Mathematical Imaging and Vision Year : 2013

A parallel proximal splitting method for disparity estimation from multicomponent images under illumination variation

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 reg- ularity on the solution. Experiments demonstrate that the method is efficient and provides better results compared with other approaches.
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Dates and versions

hal-00733454 , version 1 (19-09-2012)

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Caroline Chaux, Mireille El Gheche, Joumana Farah, Jean-Christophe Pesquet, Beatrice Pesquet-Popescu. A parallel proximal splitting method for disparity estimation from multicomponent images under illumination variation. Journal of Mathematical Imaging and Vision, 2013, 47 (3), pp.167-178. ⟨10.1007/s10851-012-0361-z⟩. ⟨hal-00733454⟩
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