
Proceedings Paper
Real-time video coding under power constraint based on H.264 codecFormat | Member Price | Non-Member Price |
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Paper Abstract
In this paper, we propose a joint power-distortion optimization scheme for real-time H.264 video encoding under the
power constraint. Firstly, the power constraint is translated to the complexity constraint based on DVS technology.
Secondly, a computation allocation model (CAM) with virtual buffers is proposed to facilitate the optimal allocation of
constrained computational resource for each frame. Thirdly, the complexity adjustable encoder based on optimal motion
estimation and mode decision is proposed to meet the allocated resource. The proposed scheme takes the advantage of
some new features of H.264/AVC video coding tools such as early termination strategy in fast ME. Moreover, it can
avoid suffering from the high overhead of the parametric power control algorithms and achieve fine complexity
scalability in a wide range with stable rate-distortion performance. The proposed scheme also shows the potential of a
further reduction of computation and power consumption in the decoding without any change on the existing decoders.
Paper Details
Date Published: 29 January 2007
PDF: 12 pages
Proc. SPIE 6508, Visual Communications and Image Processing 2007, 650802 (29 January 2007); doi: 10.1117/12.703686
Published in SPIE Proceedings Vol. 6508:
Visual Communications and Image Processing 2007
Chang Wen Chen; Dan Schonfeld; Jiebo Luo, Editor(s)
PDF: 12 pages
Proc. SPIE 6508, Visual Communications and Image Processing 2007, 650802 (29 January 2007); doi: 10.1117/12.703686
Show Author Affiliations
Li Su, Microsoft Research Asia (China)
Yan Lu, Microsoft Research Asia (China)
Feng Wu, Microsoft Research Asia (China)
Yan Lu, Microsoft Research Asia (China)
Feng Wu, Microsoft Research Asia (China)
Shipeng Li, Microsoft Research Asia (China)
Wen Gao, Graduate School, Chinese Academy of Sciences (China)
Wen Gao, Graduate School, Chinese Academy of Sciences (China)
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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