Stereoscopic image completion and depth recovery

In this paper, we have proposed a novel patch-based method for automatic completion of stereoscopic images and the corresponding depth/disparity maps simultaneously. The missing depths are estimated in local feature space and a patch distance metric is designed to take the appearance, depth gradients and depth inconsistency into account. To ensure the proper stereopsis, we first search for the proper stereoscopic patch in both left and right images according to the distance metric, and then iteratively refine the images. Our method is capable of dealing with general scenes including both frontal-parallel and non-frontal-parallel objects. Experimental results show that our method is superior to previous ones with better stereoscopically consistent content and more plausible completion.