Adaptive motion-compensated wavelet filtering for image sequence coding

This paper deals with new advances made in the field of discrete spatio-temporal filters applied to digital image sequences. Within time-varying images, the temporal correlation of the information is folded within the spatio-temporal domain by motions originating from both camera and object displacements. The spatio-temporal video information can be therefore reformulated in terms of motion trajectories and intensity variations along these trajectories. To yield that signal description, the spatio-temporal scenes will be segmented according to motion. Motion-compensated temporal filters have been used as convolutional filters applied along the assumed motion trajectories. Spectral interpretations show the efficiency of motion-compensated filtering for video signals. As a matter of fact, the whole signal analysis performed in this paper also includes a spatial filtering to achieve a complete spatio-temporal (2-D+T) decomposition. Motion-compensated filtering leads to multiresolution applications. It leads to optimum and adaptive signal-to-noise decomposition procedures based on the temporal correlative content. Such properties allow enhancing tasks like temporal interpolation, image sequence smoothing, and restoration. Simulation results are presented in this paper to illustrate the field of image sequence coding.