Title from e-book title screen (viewed Mar. 17, 2008).

Includes bibliographical references and index.

Digital ridgelet transform based on true ridge functions / D.L. Donoho and A.G. Flesia -- Digital implementation of ridgelet packets / A.G. Flesia, H. Hel-or, A. Averbuch, E.J. Candès, R.R. Coifman and D.L. Donoho -- Brushlets : steerable wavelet packets / François G. Meyer and Ronald R. Coifman -- Contourlets / M.N. Do and M. Vetterli -- Eno-Wavelet transforms and some applications / Tony F. Chan and Hao-Min Zhou -- A mechanical image model for Bayesian tomographic reconstruction / Shiying Zhao and Haiyan Cai -- Recent development of spline wavelet frames with compact support / Charles Chui and Joachim Stöckler -- Affine, quasi-affine and co-affine wavelets / Philip Gressman, Demetrio Labate, Guido Weiss and Edward N. Wilson -- Sparsity vs. statistical independence in adaptive signal representations : a case study of the spike process / Bertrand Bénichou and Naoki Saito -- Nonuniform filter banks : new results and open problems / Sony Akkarakaran and P.P. Vaidyanathan.

"Beyond Wavelets" presents state-of-the-art theories, methods, algorithms, and applications of mathematical extensions for classical wavelet analysis. Wavelets, introduced 20 years ago by Morlet and Grossmann and developed very rapidly during the 1980's and 1990's, has created a common link between computational mathematics and other disciplines of science and engineering. Classical wavelets have provided effective and efficient mathematical tools for time-frequency analysis which enhances and replaces the Fourier approach. However, with the current advances in science and technology, there is an immediate need to extend wavelet mathematical tools as well. "Beyond Wavelets" presents a list of ideas and mathematical foundations for such extensions, including: continuous and digital ridgelets, brushlets, steerable wavelet packets, contourlets, eno-wavelets, spline-wavelet frames, and quasi-affine wavelets. Wavelet subband algorithms are extended to pyramidal directional and nonuniform filter banks. In addition, this volume includes a method for tomographic reconstruction using a mechanical image model and a statistical study for independent adaptive signal representation. Investigators already familiar with wavelet methods from areas such as engineering, statistics, and mathematics will benefit by owning this volume. *Curvelets, Contourlets, Ridgelets, *Digital Implementation of Ridgelet Packets *Steerable Wavelet Packets *Essentially Non-Oscillatory Wavelets *Medical Imaging *Non-Uniform Filter Banks *Spline-wavelet frames and *Vanishing Moment Recovery Functions.

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