Complexity scalable motion estimation for H.264/AVC
Changsung Kim, Jun Xin, Anthony Vetro, C.‐C. Jay Kuo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
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.