Block-adaptive palette-based prediction for depth map coding

This paper proposes a novel prediction scheme for depth map coding. We utilize the fact that depth values are largely dependent on objects and one small block consists of only a small number of objects at most. The proposed method approximates each block with one palette and one object shape map. The palette consists of two representative depth values for foreground object and background object in the target block. The object shape map expresses which object exists at each pixel. These data are encoded only at the blocks where the proposed method is used. In order to reduce the bitrates required to transfer palettes and object shape maps, the proposed method enables their prediction by utilizing spatial and temporal correlations. Experiments are conducted on three kinds of depth maps; estimated from multiview images, captured by special sensors, and generated by computer. The results show that the proposed method reduces the bitrate by up to 40% and about 20% on average for 13 sequences relative to the MPEG-4 AVC/H.264.