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

作者：Chaux C^*; El Gheche M; Farah J; Pesquet J C; Pesquet Popescu B

来源：Journal of Mathematical Imaging and Vision, 2013, 47(3): 167-178.

DOI：10.1007/s10851-012-0361-z

• Stereo
• Disparity
• Color images
• Illumination variation
• Proximity operator
• Total variation
• Tight frame
• Convex optimization
• Parallel proximal algorithms

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.

• 出版日期2013-11