This paper describes low rate FGS video compression algorithms
based on closed-loop temporal prediction combined with motion-compensated spatio-temporal wavelet analysis. After presenting an overall coding architecture, the paper reviews different motion-compensated (MC) temporal filtering solutions and discusses their amenability for compression and fine grain scalability. The coding architecture relies on a rate-constrained hierarchical motion estimation and a 3D-EBCOT algorithm. The analysis of different MC-temporal filtering solutions is substantiated with various quantitative elements on filter length, on motion models and temporal transform reliability. Some of their limitations are then addressed by designing algorithms which combine closed-loop temporal prediction with MC-temporal analysis. The PSNR performances of the approaches are compared with those obtained with MPEG-4 part 2 and H.264 JM2.1.