基于非对称的三步搜索算法的运动估计

Motion Estimation Based on Asymmetric Three-Step Search Algorithm

针对运动估计过程中传统的三步搜索算法的时间复杂度高的问题,提出了基于非对称的三步搜索算法的运动估计研究.首先将每帧图像按16×16的大小划分宏块作为压缩基本单元;然后,以当前宏块的中心点为中心,用非对称三步搜索算法搜索最佳匹配块的中心点,得到运动矢量;最后,对运动矢量进行编码作为压缩存储数据.实验表明:此算法与传统的全搜索、三步搜索算法相比,图像恢复后的信噪比相当;搜索时间比全搜索平均节约了67%,比三步搜索算法平均节约了40%;搜索点数比全搜索平均减少了89%,比三步搜索算法平均减少了6.5%.

Aiming at the high time complexity of the traditional three-step search algorithm in the motion estimation process, a motion estimation research based on the asymmetric three-step search algorithm is proposed. First, the image is divided into 16×16 macroblocks as the basic unit of compression. Second, center point of the current macroblock is taken as the center, and the center point of the best matching block is searched using the asymmetric three-step search algorithm to obtain the motion vector. Finally, the Motion vectors are encoded as compressed storage data. Experiments show that compared with the traditional full-search and three-step search algorithms, the proposed algorithm has a similar SNR after image recovery. The search time is saved by 67% compared with the full search, and it is saved by an average of 40% compared with the three-step search algorithm. The number of search points has been reduced by an average of 89% compared with the full search, and has been reduced by an average of 6.5% compared with the three-step search algorithm.