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Proceedings Paper

Fast prediction algorithm of adaptive GOP structure for SVC
Author(s): Yi-Hau Chen; Chia-Hua Lin; Ching-Yeh Chen; Liang-Gee Chen
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Paper Abstract

Adaptive group-of-picture (GOP) structure is an important encoding tool in multi-level motion-compensated temporal filtering coding scheme. Compared to conventional fixed-GOP scheme, it can dynamically adapt the GOP size to enhance the coding performance based on each sequence's characteristics. But the existing adaptive GOP structure (AGS) algorithm proposed in JSVM requires huge computation complexity. In this paper, a fast AGS prediction algorithm is proposed. At first, based on the relationship among coding performance, GOP size and corresponding intra block ratio, a sub-GOP size prediction model for different decomposition levels is developed based on the encoded intra block ratio. Then, a prediction scheme is proposed to implement AGS by the sub-GOP size prediction model. It can predict the following sub-GOP size by current sub-GOP's information instead of searching all possible sub-GOP composition. The experimental results show that the proposed algorithm with linear threshold has almost equivalent coding performance as AGS in JSVM but only one-fourth computation complexity for 4-level interframe coding scheme is required.

Paper Details

Date Published: 29 January 2007
PDF: 9 pages
Proc. SPIE 6508, Visual Communications and Image Processing 2007, 65080U (29 January 2007); doi: 10.1117/12.703484
Show Author Affiliations
Yi-Hau Chen, National Taiwan Univ. (Taiwan)
Chia-Hua Lin, National Taiwan Univ. (Taiwan)
Ching-Yeh Chen, National Taiwan Univ. (Taiwan)
Liang-Gee Chen, National Taiwan Univ. (Taiwan)


Published in SPIE Proceedings Vol. 6508:
Visual Communications and Image Processing 2007
Chang Wen Chen; Dan Schonfeld; Jiebo Luo, Editor(s)

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