块匹配运动估计在视频编码中有着举足轻重的地位，其性能的优劣在很大程度上影响着输出码流的质量。全搜索是效果最好的运动估计算法，但其巨大的运算量是实际应用，特别是实时应用无法承受的。为解决这一问题，各种快速算法不断涌现。本文提出了一种适用于最新视频编码标准——H．264／MPEG4-AVC的快速运动估计算法。该算法基于自适应搜索范围，利用视频图像序列的帧间统计特性以及运动向量时域、空域的相关性，在保证PSNR性能的同时，使运动估计部分的运算复杂度大为降低。实验仿真表明，该算法适用面广，对大运动与小运动序列都有很强的自适应能力。在保持与全搜索相同PSNR的同时，平均速度超过全搜索280倍有余，超过三步法1．8倍，性能明显优于新三步法、四步法等经典快速运动估计算法。

Block matching motion estimation (BMME) plays a very important role in video coding. The performance of BMME greatly affects the quality of the encoded bit stream. Full Search (FS) is the optimal algorithm for BMME. But the tremendous computation payload of it is unaffordable for practical applications, especially for real time applications. To overcome this problem, a lot of fast algorithms were developed. In this paper, a novel fast motion estimation algorithm designed for the new video coding standard H.264/MPEG 4 AVC is proposed. Based on an adaptive search range, the proposed algorithm makes use of the statistical characteristics between successive frames and the spatial and temporal correlations among the motion vectors of adjacent blocks to speed the process of motion estimation while maintaining the PSNR with no loss. The simulation results show that the algorithm is able to fit for all types of video sequences adaptively in spite of the degree of the motions. Compared with other algorithms, it is more than 280 times faster than FS (Full Search) and more than 1.8 times faster than 3SS (3 Steps Search) in average with no PSNR loss. And it is a better one than the traditional fast motion estimation algorithms, such as N3SS (New 3 Steps Search) and 4SS (4 Steps Search).