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Proceedings Paper

Complexity scalable motion estimation for H.264/AVC
Author(s): Changsung Kim; Jun Xin; Anthony Vetro; C.-C. Jay Kuo
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Paper Abstract

A new complexity-scalable framework for motion estimation is proposed to efficiently reduce the motioncomplexity of encoding process, with focus on long term memory motion-compensated prediction of the H.264 video coding standard in this work. The objective is to provide a complexity scalable scheme for the given motion estimation algorithm such that it reduces the encoding complexity to the desired level with insignificant penalty in rate-distortion performance. In principle, the proposed algorithm adaptively allocates available motion-complexity budget to macroblock based on estimated impact towards overall rate-distortion (RD) performance subject to the given encoding time limit. To estimate macroblock-wise tradeoff between RD coding gain (J) and motion-complexity (C), the correlation of J-C curve between current macroblock and collocated macroblock in previous frame is exploited to predict initial motion-complexity budget of current macroblock. The initial budget is adaptively assigned to each blocksize and block-partition successively and motion-complexity budget is updated at the end of every encoding unit for remaining ones. Based on experiment, proposed J-C slope based allocation is better than uniform motion-complexity allocation scheme in terms of RDC tradeoff. It is demonstrated by experimental results that the proposed algorithm can reduce the H.264 motion estimation complexity to the desired level with little degradation in the rate distortion performance.

Paper Details

Date Published: 19 January 2006
PDF: 12 pages
Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60770A (19 January 2006); doi: 10.1117/12.648539
Show Author Affiliations
Changsung Kim, Univ. of Southern California (United States)
Jun Xin, Mitsubishi Electric Research Labs. (United States)
Anthony Vetro, Mitsubishi Electric Research Labs. (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 6077:
Visual Communications and Image Processing 2006
John G. Apostolopoulos; Amir Said, Editor(s)

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