Geometry-based Block Partitioning for Efficient Intra Prediction in Depth Video Coding

摘要

In the 3D video system including depth information, once a depth video is coded by the state-of-the-art video compression tools such as H.264/AVC, depth errors around the boundaries of objects can be intensified, and these can significantly affect the quality of rendered virtual view later. Despite this drawback of depth video coding, its compression is essential because of the enormous amount of input data in the 3D video system. In this paper, we propose a line-based partitioned intra prediction method which exploits geometric redundancy of depth video for an efficient compression without significant errors around boundaries. The proposed algorithm can efficiently divide the current coded block into two partitioned regions, and the algorithm independently predicts each region with previously coded neighboring pixels. Finally, the generated prediction mode adaptively alternates the conventional DC intra prediction mode. To evaluate the intra prediction performances, we have implemented the proposed method into H.264/AVC intra prediction scheme. Experimental results have demonstrated that our proposed method provides higher coding performance. The coding performance for depth video compression itself was up to 4.43% bit-saving or 0.526 dB gain in terms of peak signal-to-noise ratio (PSNR) among proper depth sequences which contain line-like boundaries.