Motion Estimation based on Artificial Fish-Swarm in H.264/AVC Coding

Motion estimation plays a key role in H.264/AVC video coding, but it is the most time-consuming task in the encoding process. In order to reduce the computational complexity of motion estimation in H.264/AVC video coding, this paper proposes a new search algorithm based on artificial fish-swarm algorithm (AFSA) which is a new efficient optimizing method. Firstly, some characteristics of AFSA are modified, such as visual, step, moving direction and initial fish positions in order to better adapt to motion estimation. Secondly, an adaptive search strategy based on modified AFSA Algorithm is presented to further reduce computational complexity, including double search mode, dynamic search range and early termination strategy. Experimental results show that the proposed algorithm saves the average motion estimation times up 39.29% and 31.22% for UMHexagonS and EPZS algorithm, which are adopted in H.264/AVC video coding, with almost same rate distortion performance. Key-Words: motion estimation, artificial fish-swarm, optimizing method, H.264/AVC coding, search mode, rate distortion