A depth video processing algorithm based on cluster dependent and corner-ware filtering

In free viewpoint video system, color video and the associated depth video are utilized to synthesize arbitrary virtual viewpoint. Hence, high quality of depth video is a necessity for virtual view rendering. However, depth video estimated by depth estimate software is inconsistent and inaccurate which decreases the quality of virtual views. To solve the problem, a depth video processing algorithm is proposed in this paper. Firstly, depth video is divided into five clusters adaptively by Fuzzy C-means clustering method. Meanwhile, the edges of depth video are detected and expanded into 8×8 block-wise. Secondly, for pixels in non-edge regions of depth video, a cluster dependent filtering method is adopted according to the feature of each cluster. Finally, corners in the corresponding texture video are detected. For pixels in edge regions of depth video, a corner-aware filtering method is used. Experimental results show that the proposed algorithm enhances the depth video and significantly improves the quality of the virtual views. The peak signal to noise ratio of virtual views rendered by using the proposed algorithm is 0.43 dB higher than that of the virtual views rendered by using the original depth video. The proposed algorithm also outperforms Martin's algorithm in terms of virtual view rendering performance.