Despite their novelty, wavelets have a tremendous impact on a number of
modern scientific disciplines, particularly on signal and image
analysis. Because of their powerful underlying mathematical theory, they
offer exciting opportunities for the design of new multi-resolution
processing algorithms and effective pattern recognition systems.
This book provides a much-needed overview of current trends in the
practical application of wavelet theory. It combines cutting edge
research in the rapidly developing wavelet theory with ideas from
practical signal and image analysis fields. Subjects dealt with include
balanced discussions on wavelet theory and its specific application in
diverse fields, ranging from data compression to seismic equipment. In
addition, the book offers insights into recent advances in emerging
topics such as double density DWT, multiscale Bayesian estimation,
symmetry and locality in image representation, and image fusion.
Audience: This volume will be of interest to graduate students and
researchers whose work involves acoustics, speech, signal and image
processing, approximations and expansions, Fourier analysis, and medical
imaging