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Efficient Intra Mode Selection for Depth-Map Coding Utilizing Spatiotemporal, Inter-Component and Inter-View Correlations in 3D-HEVC.

Authors :
Shen, Liquan
Li, Kai
Feng, Guorui
An, Ping
Liu, Zhi
Source :
IEEE Transactions on Image Processing; Sep2018, Vol. 27 Issue 9, p4195-4206, 12p
Publication Year :
2018

Abstract

3D-high efficiency video coding (HEVC) is developed for the compression of the multi-view video plus depth format, which is based on the latest generation of video coding standard, HEVC. It further adopts several new intra prediction modes, depth-modeling modes (DMMs) in intra candidate modes for a better representation of edges in depth maps, which introduces a drastic increase in the computational complexity. The procedure of depth intra mode decision together with DMMs and existing intra modes is a very time consuming part due to huge complexity of full rate distortion (RD) cost calculation. In this paper, a low complexity intra mode selection algorithm is proposed to reduce complexity of depth intra prediction in both intra-frames and inter-frames. An experimental analysis is first performed to study the inter-view correlation and the inter-component (texture video and its associated depth) correlation in intra coding information such as the intra mode and RD cost. All intra modes available in 3D-HEVC are classified into three activity classes assigned with different mode-weight factors, and the coding mode complexity of a coding unit (CU) is defined according to the intra mode information from available spatiotemporal, inter-view, and inter-component neighboring coded CUs. The coding mode complexity analysis is utilized to assign different candidate intra modes for different types of CUs. The optimal intra prediction mode and the RD cost value in current CU depth level are further used to skip unnecessary intra prediction sizes. Experimental results show that the proposed fast depth intra coding algorithm achieves 61% complexity reduction on intra prediction, while incurring a 0.2% Bjontegaard metric increase for coded and synthesized views compared to the test model of 3D-HEVC. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10577149
Volume :
27
Issue :
9
Database :
Complementary Index
Journal :
IEEE Transactions on Image Processing
Publication Type :
Academic Journal
Accession number :
129967101
Full Text :
https://doi.org/10.1109/TIP.2018.2837379