Video Compression with Wavelet Transform Using WBM Method and SPIHT Algorithm
Now a day video processing became very popular on the contrary video content require very large storage area. To the benefit of reduce storage area we need to remove redundant data. In this practice we need to estimate the motion vectors to preserve quality. Motion vector estimation is the heart of the video processing. Conversely the mechanism of motion vector estimation normally suffers from the problems such as ambiguities of motion trajectory and illumination variances. In this paper we presents a new approach using Wavelet domain Block Matching (WBM) method and Set Partitioning In Hierarchical Trees (SPIHT) algorithm for video compression. And measured performance using parameters like mean squared error (MSE), peak signal to noise ratio (PSNR), compression ratio and structural similarity index (SSIM).
S.Swarna Latha, P.V.Lakshman Kumar