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 motion-selective sub band decomposition for video signals. We demonstrate the potential of this new technique in a video denoising application.
Cite this article:
Chhabikiran Sao , Amit Kolhe. Video Compression with Wavelet Transform Using SPIHT Algorithm in MATLAB Simulink. Research J. Engineering and Tech. 2(3): July-Sept. 2011 page 123-127.