Classified-edge guided depth resampling for multi-view coding

Abstract

A new depth resampling for multi-view coding is proposed in this paper. At first, the depth video is downsampled by median filtering before encoding. After decoding, the classified edges, including credible edge and probable edge from the aligned texture image and the depth image, are interpolated by the selected diagonal pair, whose intensity difference is the minimum among four diagonal pairs around edge pixel. According to different category of edge, the intensity difference is measured by either real depth or percentage depth without any parameter setting. Finally, the resampled depth video and the decoded full-resolution texture video are synthesized into virtual views for the performance evaluation. Experiments on the platform of multi-view high efficiency video coding (HEVC) demonstrate that the proposed method is superior to the contrastive methods in terms of visual quality and rate distortion (RD) performance.

Keywords

Depth Image / High Efficiency Video Code / Virtual View / Texture Video / Depth Video

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