Motion estimation is a common ingredient in many state-of the-art video processing algorithms, serving as an effective way to capture the spatial-temporal correlation in video signals. However, the robustness of motion estimation often suffers from problems such as ambiguities of motion trajectory (i.e. the aperture problem) and illumination variances. In this paper, we explore a new framework for video processing based on the recently proposed wavelet transform with SPIHT algorithm. Instead of containing an explicit motion estimation step, the wavelet transform provides motionselective sub band decomposition for video signals. We demonstrate the potential of this new technique in a video denoising application.
Motion estimation, Spatial, temporal, trajectory, decomposition, denoising
