Wavelet-constrained stereo matching under photometric variations
Wided Miled, Jean‐Christophe Pesquet, Michel Parent · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
We propose a new method to address the problem of stereo matching under varying illumination conditions. First, a spatially varying multiplicative model is developed to account for photometric changes induced between both images in the stereo pair. The stereo matching problem based on this model is then formulated as a constrained optimization problem in which an appropriate convex objective function is minimized under convex constraints. These constraints arise from prior knowledge and rely on various properties of both disparity and illumination fields. In order to obtain a smooth disparity field while preserving discontinuities around object edges, we consider an appropriate wavelet-based regularization constraint. The resulting multi-constrained optimization problem is solved via an efficient block iterative algorithm which offers great flexibility in the incorporation of several constraints. Experimental results demonstrate the efficiency of the proposed method to recover illumination changes and disparity map simultaneously, making stereo matching very robust w.r.t. such changes.