Speech and Image Compression Using Discrete Wavelet Transform
N.A. Junejo, Nasir Udin Ahmed, Mukhtiar Ali Unar, Arjun Rajput · 2006
Efficient speech and image compression solutions are becoming critical with the recent growth of data intensive, multimedia based applications. In this paper, we describe the application of the discrete wavelet transform (DWT) for analysis, processing and compression of multimedia signals like speech and image. More specifically we explore the major issues concerning the wavelet based speech and image compression which include choosing the optimal wavelet, decomposition levels and thresholding criteria. The simulation results prove the effectiveness of DWT based techniques in attaining an efficient compression ratio of 2.31 for speech and 2.67 for images, achieving higher signal to noise ratio (SNR), better peak signal to noise ratio (PSNR), while the retained signal energy is 99.9885% and the resulting signals are generally much smoother