Wavelets in Signal and Image Analysis: From Theory to Practice by A.A. PetrosianWavelets in Signal and Image Analysis: From Theory to Practice by A.A. Petrosian

Wavelets in Signal and Image Analysis: From Theory to Practice

EditorA.A. Petrosian, F.G. Meyer

Paperback | December 5, 2010

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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.
Title:Wavelets in Signal and Image Analysis: From Theory to PracticeFormat:PaperbackDimensions:556 pages, 9.45 × 6.3 × 0.04 inPublished:December 5, 2010Publisher:Springer NetherlandsLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9048158389

ISBN - 13:9789048158386

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Table of Contents

Preface. Part I: Wavelet Design. 1. Discrete-Time Wavelets; M. Doroslovacki. 2. The Double Density DWT; I.W. Selesnick. Part II: Multiscale Analysis, Estimation and Filtering. 3. Multiscale Bayesian Estimation and Data Rectification; S. Ungarala, B.R. Bakshi. 4. Empirical Tests for Evaluation of Multirate Filter Bank Parameters; C. Taswell. 5. Symmetry and Locality in Image Representation; R. Wilson. 6. Towards Bridging Scale-Space and Multiscale Frame Analyses; Y. Bao, H. Krim. 7. Wavelet Domain Features for Texture/Pattern Description, Classification and Replicability Analysis; L. Balmelli, A. Mojsilovic. 8. Wavelets for Image Fusion; S. Nikolov. Part III: Signal and Image Compression. 9. Transform Coding of Signals with Bounded Finite Differences: from Fourier to Walsh, to Wavelets; A. Petrosian. 10. Multi-layered Image Representation; F.G. Meyer, et al. 11. Image Compression Through Level Lines and Wavelet Packets; J. Froment. 12. Image Compression Using Spline Based Wavelet Transforms; A.Z. Averbuch, V.A. Zheludev. Part IV: Applications in Biomedicine and other Fields. 13. Spatio-Temporal Directional Analysis of Real-Time Three-Dimensional Cardiac Ultrasound; E. Angelini, A. Laine. 14. Wavelets for Computer-Aided Diagnosis in Radiographic Images; H. Yoshida. 15. Wavelet Analysis of Event Related Potentials for Early Diagnosis of Alzheimer's Disease; R. Polikar, et al. 16. An Application of the DWT in Seismic Data Analysis; P.J. Oonincx, et al. 17. Application of Wavelet Analysis to Condition Monitoring of Electromechanical Equipment; P. Kang.