Stochastic Modeling of the Spatiotemporal Wavelet Coefficients and Applications to Quality Enhancement and Error Concealment

Abstract

We extend a stochastic model of hierarchical dependencies between wavelet coefficients of still images to the spatiotemporal decomposition of video sequences, obtained by a motion-compensated wavelet decomposition. We propose new estimators for the parameters of this model which provide better statistical performances. Based on this model, we deduce an optimal predictor of missing samples in the spatiotemporal wavelet domain and use it in two applications: quality enhancement and error concealment of scalable video transmitted over packet networks. Simulation results show significant quality improvement achieved by this technique with different packetization strategies for a scalable video bit stream.

Keywords

• wavelets
• spatiotemporal decompositions
• stochastic modeling
• hierarchical dependencies
• video quality
• scalability