针对现有细粒度视频编码算法计算复杂度大或视频恢复质量有各种效应的缺点，提出了一种基于联合小波变换和MP变换的细粒度编码算法。该算法在运动估计与补偿的基础上，用小波变换来消除帧间冗余，然后对变换结果根据不同帧的数据特征分别进行二维小波变换或MP变换。算法还提出了新的运动估计和像素调整策略、基于人眼视觉特性的MP原子分配策略和基于能量查找的原子搜索机制。实验表明，该算法可同时兼顾视频恢复质量、计算复杂度和控制粒度。

With the widespread development of video applications, it is very urgent to develop fine granular scalable video compression algorithms, among which discrete wavelet transformation and matching pursuit (MP) transformation are the most popular. However, the complexity of MP video coding and the ringing and rippling of discrete wavelet transform video coding are annoying obstacles to many video applications. In this context, an algorithm based on both discrete wavelet and MP transform is presented in this paper for fine granularity video coding. Firstly, using every eight frames as a unit, this algorithm applies motion prediction and eliminates the inter frame redundancy by 1-dimensional wavelet transformation at motion vector direction. Thus, 1 low-frequency and 7 high-frequency frames are obtained. The transformed low-frequency frame is further processed by 2-dimensional wavelet transformation to eliminate the intra frame redundancy, with the other 7 high-frequency frames coded by Matching Pursuit. A new motion prediction and pixels regulation strategy is also presented in this paper. The MP atom assignment is based on human eye's vision characteristics and the energy of residual after motion estimation. The experiments on its performance and the analysis of computing complexity indicate that this algorithm balances the recovery video quality, computation complexity, and control granularity.