JOURNAL ARTICLE

Distributed multi-view video coding

Xun GuoYan LuFeng WuWen GaoShipeng Li

Year: 2006 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 6077 Pages: 60770T-60770T   Publisher: SPIE

Abstract

There are mainly two key points which can affect the efficiency of multi-view video capture and transmission system largely: communication between cameras and computing complexity of encoder. In this paper, we propose a practical framework of distributed multi-view video coding, in which inter-camera communication is avoided and the large computing complexity is moved from encoder to decoder. In this scheme, multi-camera video sources are encoded separately and decoded dependently, and the traditional inter frame is replaced by Wyner-Ziv frame. To reach this goal, Wyner-Ziv theory on source coding with side information is employed as the basic coding principle. A Wyner-Ziv coding method based on wavelet transform and turbo codes is used as the core of the scheme. To further improve the coding performance, we also consider exploiting the large redundancy between adjacent views. A more flexible prediction method that can jointly use temporal and view correlations is proposed to generate the side information at the decoder. The experimental results show that the coding performance of proposed DMVC scheme is very promising compared to the traditional intra coding.

Keywords:
Distributed source coding Computer science Encoder Coding tree unit Coding (social sciences) Context-adaptive binary arithmetic coding Tunstall coding Theoretical computer science Variable-length code Shannon–Fano coding Decoding methods Algorithm Sub-band coding Multiview Video Coding Computer vision Data compression Speech recognition Video processing Video tracking Speech coding Mathematics

Metrics

90
Cited By
16.13
FWCI (Field Weighted Citation Impact)
7
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Wireless Communication Security Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics

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