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.