Depth coding in 3D-HEVC deforms object shapes due to block-level edge-approximation and lacks efficient techniques to exploit the statistical redundancy, due to the framelevel clustering tendency in depth data, for higher coding gain at near-lossless quality. This paper presents a standalone monoview depth sequence coder, which preserves edges implicitly by limiting quantisation to the spatial-domain and exploits the frame-level clustering tendency efficiently with a novel binary tree based decomposition (BTBD) technique. BTBD can exploit the statistical redundancy in frame-level syntax, motion components, and residuals efficiently with fewer block-level prediction/coding modes and simpler context modelling for context-adaptive arithmetic coding. Compared to the depth coder in 3D-HEVC, the proposed one has achieved significantly lower bitrate at lossless to near-lossless quality range for mono-view coding and rendered superior quality synthetic views from the depth maps, compressed at the same bitrate, and the corresponding texture frames.
|Number of pages||15|
|Journal||IEEE Transactions on Circuits and Systems for Video Technology|
|Early online date||04 Feb 2019|
|Publication status||Published - Mar 2020|
Shahriyar, S., Murshed, M., Ali, M., & Paul, M. (2020). Depth Sequence Coding with Hierarchical Partitioning and Spatial-domain Quantization. IEEE Transactions on Circuits and Systems for Video Technology, 30(3), 835-849. https://doi.org/10.1109/TCSVT.2019.2897403