中文摘要：

首先提出了一种运动估计方法MLBS（Modified Low Band Shift），并在此基础上提出了基于MLBS的小波域视频可分级运动估计方案MLBSSME．利用MLBS方法，提高了运动估计的准确度．借助重叠块运动补偿方法，有效降低了最高分辨率下解码图像的块效应．根据小波变换的多分辨率特性，利用缩小了的搜索窗口提高了搜索速度．这种方法可有效应用于空间可分级和数率可分级的视频编码器中．实验结果证明，对于多种类型的标准测试视频流，MLBSSME算法始终能保持很高的估计精度．利用该算法补偿得到的预测帧，其PSNR较之基于下层LL子带的分层运动估计方法和子带直接运动估计方法平均要高出1～3dB，而对于空间细节较简单的视频，其PSNR比LBS方法提高了0．5～1dB，并且算法的时空复杂度是LBS方法复杂度的30％～40％．

英文摘要：

This paper firstly proposes a new motion estimation method MLBS （Modified Low Band Shift）, and then puts forward an MLBS based scalable video motion estimation scheme in the wavelet domain （MLBSSME）. The modified low band shift method improves the accuracy of the motion estimation. And the ＂blocking artifacts＂ at the finest resolution are effectively reduced by overlapped block motion compensation technique. According to the multi-resolution representation characteristics of wavelet transform, the estimation process is limited in a search window of reduced size so that the search speed is accelerated. The proposed scheme can be effectively applied to spatial scalable and rate scalable video codec. The simulation results show that the MLBSSME scheme can always reach high motion estimation accuracy for standard test video sequences which have different characteristics respectively. And the proposed scheme can achieve 1-3dB higher prediction quality on average than the next-finer-resolution LL subband based hierarchical motion estimation algorithm and the band-to-band motion estimation algorithms, and 0. 5-1dB higher prediction quality than LBS method when the spatial detail of the source video is low. Moreover, the time and space complexity of the proposed scheme is only 30%～40% as much as the complexity of LBS.