Fast Multi-Reference Frame Motion Estimation via Downhill Simplex Search

Multi-reference frame motion estimation improves the accuracy of motion compensation in video compression, but it also dramatically increases computational complexity. Based on tracing motion vector trajectories, fast approximated motion estimation results can be obtained for multi-reference frames. In this paper, we extend the downhill simplex search to multiple reference frames and propose several enhanced schemes to improve its efficiency and accuracy. Experimental results show that the proposed algorithm outperforms several representative single-reference frame block matching methods