一种有效的自适应运动估计搜索算法

Efficient adaptive motion estimation search algorithm

提出了一种新的基于运动矢量场、方向自适应和半像素搜索的快速搜索算法(M-DAHS)。该算法根据图像序列运动矢量场的中心偏置性和时空相关性进行预判,对静止块设定阈值直接终止搜索;非静止块根据运动类型自适应选择搜索起始点和搜索策略。搜索模板具有很强的方向自适应性,对于小运动块采用菱形-线性搜索,其他块使用六边形-菱形搜索算法。整像素搜索完毕后,再以十字优先原则进行半像素搜索。实验结果表明,该算法性能优越,搜索速度快,搜索精度高,且搜索精度可以非常接近全搜索算法。

A novel fast motion estimation algorithm called M-DAHS based on motion vector field, adaptive direction and half-pixel search was proposed. According to center-bias property and spatial-temporal correlation of the vector field, the threshold was applied to stop the stationary block from searching. The initial search point and strategy were adaptively selected based on motion type for non-stationary block. The search template has strong direction adaptability. The line-diamond search was used for the blocks with low motion activity, and the hexagon-diamond search for that with middle or high motion. After searching all the pixels, a cross priority search pattern was utilized for half-pixel search. Experimental results show that the proposed algorithm has good performance with high search speed and high precision, while the distortion is almost the same as full search algorithm.