Efficient depth map recovery using concurrent object boundaries in texture and depth images
An efficient depth map recovery algorithm, using concurrent object boundaries in texture and depth signals, is proposed in this work. We first analyze the effects of a distorted depth map on the qualities of synthesized views. Based on the analysis, we propose an object boundary detection scheme to restore sharp boundaries from a distorted depth map. Specifically, we initially estimate object boundaries from a depth map using the gradient magnitude at each pixel. We then multiply the gradient magnitudes of texture and depth pixels. Then, we suppress boundary pixels with non-maximum magnitudes and refine the object boundaries. Finally, we filter depth pixels along the gradient orientations using a median filter. Experimental results show that the proposed algorithm significantly improves the qualities of synthesized views, as compared with conventional algorithms.