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Lossy Image Compression Using Wavelets
Authors:Nick D. Panagiotacopulos  Ken Friesen  Sukit Lertsuntivit
Affiliation:(1) Department of Electrical Engineering, College of Engineering, California State University, Long Beach, CA, 90840, U.S.A.
Abstract:In this paper, we report the results of the application of transform coding image data compression techniques using Daubechies and Coifman wavelets. More specifically, D2, D4, D8, D16, and C6, C12 wavelets were used. The results from these wavelets were compared with those of discrete cosine transform. They clearly demonstrated the superiority of the wavelet-based techniques both in compression ratios and image quality, as well as in computational speed. Two quantization methods were used: non-uniform scalar quantization and pseudo-quantization. Both produced satisfactory results (86–88% compression ratio, and acceptable image quality).
Keywords:wavelet  wavelet function  multiresolution analysis (MRA)  filter banks  lossy compression  scaling functions  dilation equation  pseudo-quantization
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