This volume explains how the recent advances in wavelet analysis provide new means for multiresolution analysis and describes its wide array of powerful tools. The book covers variations of the windowed Fourier transform, constructions of special waveforms suitable for specific tasks, the use of redundant representations in reconstruction and enhancement, applications of efficient numerical compression as a tool for fast numerical analysis, and approximation properties of various waveforms in different contexts.
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Signal and Image Representation in Combined Spaces is the seventh volume in this popular series of WAVELET ANALYSIS AND IT APPLICATIONS. Compiled and edited by two of the foremost authorities in the field of wavelt signal representations and analyses, this book is designed to explore the wide range of powerful tools provided by the wavelet and Gabor approaches to signal and image processing. Main topics of current interest, including adaptive waveform representation, time-frequency and time-scale tools, subband image coding, and efficient numerical algorithms are contributed by leading experts such as Beylkin, Benedetto, Chui, Cohen, Coifman, Mallat, Vetterli, and Zeevi. Written for both engineers and mathematicians, this book provides state-of-the-art information for researchers and users, putting the reader in the forefront of current research and technology development.
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