Depth Sequence Coding with Hierarchical Partitioning and Spatial-domain Quantisation
Shampa Shahriyar (1), Manzur Murshed (2), Mortuza Ali (2), Manoranjan, Paul (3) ((1) Monash University, Australia, (2) Federation University, Australia, (3) Charles Sturt University, Australia)

TL;DR
This paper introduces a novel depth sequence coding method using hierarchical partitioning and spatial-domain quantisation, achieving superior compression and quality preservation over existing 3D-HEVC standards.
Contribution
It presents a standalone depth coder that exploits clustering at frame-level with a binary tree decomposition, improving lossless and near-lossless compression.
Findings
42.2x lossless compression ratio against 3D-HEVC
79.4% near-lossless bitrate reduction compared to 3D-HEVC
Enhanced quality of synthetic views in view-synthesis applications
Abstract
Depth coding in 3D-HEVC for the multiview video plus depth (MVD) architecture (i) deforms object shapes due to block-level edge-approximation; (ii) misses an opportunity for high compressibility at near-lossless quality by failing to exploit strong homogeneity (clustering tendency) in depth syntax, motion vector components, and residuals at frame-level; and (iii) restricts interactivity and limits responsiveness of independent use of depth information for "non-viewing" applications due to texture-depth coding dependency. This paper presents a standalone depth sequence coder, which operates in the lossless to near-lossless quality range while compressing depth data superior to lossy 3D-HEVC. It preserves edges implicitly by limiting quantisation to the spatial-domain and exploits clustering tendency efficiently at frame-level with a novel binary tree based decomposition (BTBD) technique.…
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Taxonomy
TopicsVideo Coding and Compression Technologies · Advanced Vision and Imaging · Advanced Image Processing Techniques
