Depth estimation with cascade occlusion culling filter for light-field cameras

摘要

Depth recovery from a light-field camera is an essential and interesting problem. One of its most challenges is to get accurate estimation for the depth discontinuities and occluded regions. We propose a simple and efficient solution with a cascade occlusion culling filter. It is a cascade processing corresponding to the different manifestations of occlusions at ray-level, pixel-level and image-level. (i) At ray-level, any potential occluded ray will be filtered out in depth-cue responses computation, and then reliable multiple-cue cost volumes are constructed. (ii) At pixel-level, occlusions generally result in weak depth discontinuity ramp edges. These discontinuities will be preserved and enhanced by a multiple-cue cost-volume filter with edge preserving property. (iii) At image-level, occlusion is embodied in the uncertain regions. In order to obtain optimal depth estimation of uncertain regions, an iterative depth optimization framework is applied to integrate the aforementioned filtered multiple-cue cost volumes with their confidences. We show that our method has good depth-discontinuity preserving property, and is insensitive to the surface color / texture discontinuities at the same time. Experimental results on Lytro Illum camera data demonstrate the effectiveness and robustness of our method which has excellent performance in handling discontinuities and occlusions.