Stochastic modeling of the spatiotemporal wavelet coefficients and applications to quality enhancement and error concealment

作     者：Feideropoulou, G Pesquet-Popescu, B 

作者机构：Ecole Natl Super Telecommun Bretagne Signal & Image Proc Dept F-75634 Paris 13 France 

出 版 物：《EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING》 (EURASIP信号处理进展杂志)

年 卷 期：2004年第2004卷第12期

页      面：1931-1942页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：wavelets spatiotemporal decompositions stochastic modeling hierarchical dependencies video quality scalability 

摘      要：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 2D+t 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.