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Proceedings Paper

Scalable video coding based on Wyner-Ziv framework
Author(s): Guiguang Ding; Qionghai Dai; Yaguang Yin; Feng Yang
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Paper Abstract

Scalable video coding (SVC) has a great advantage due to its very easy adaptation to unpredictable bandwidth variations and network conditions. However, in some scalable video coding schemes, either a single prediction is used, which leads to either drift or coding inefficiency, or a different prediction is obtained for each reconstructed version, which leads to add complexity. So, the new techniques have to be developed to improve the performance of the SVC scheme. Wyner-Ziv coding gives us the surprising insight that efficient data compression can also be achieved by exploiting source statistics-partially or wholly-at the decoder only. Based on the Wyner-Ziv framework, Xu and Xiong proposed a Layer Wyner-Ziv scheme (LWZ) by treating a standard coded video as a base layer, and building the bit-plane enhancement layer using Wyner-Ziv coding. The LWZ scheme has error robustness and channel adaptation. However, the coding efficiency gap between the nonscalable video coding and LWZ is very large. The reason is that only the current base layer and lower enhancement layers are used as side information, and the correlation between the temporal adjacent frames isn't utilized. In order to improve the coding efficiency of LWZ, a scalable video coding based on Wyner-Ziv (SVC-WZ) is proposed in this paper. In our SVC-WZ scheme, we try to use the correlation between temporal adjacent frames rather than always use the correlation between the enhancement layers and the current base layer as SI during the enhancement layer encoding. Using the correlation between temporal adjacent frames would make SI more accurate, thus it could improve the coding efficiency. Our experimental results show that the SVC-WZ scheme can achieve consistently better coding efficiency than the LWZ scheme while keeping all the properties of LWZ.

Paper Details

Date Published: 31 July 2006
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59601K (31 July 2006); doi: 10.1117/12.631420
Show Author Affiliations
Guiguang Ding, Tsinghua Univ. (China)
Qionghai Dai, Tsinghua Univ. (China)
Yaguang Yin, Tsinghua Univ. (China)
Feng Yang, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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