Discovering Wavelets

by ;
Edition: 1st
Format: Hardcover
Pub. Date: 1999-10-05
Publisher(s): Wiley-Interscience
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Summary

An accessible and practical introduction to wavelets With applications in image processing, audio restoration, seismology, and elsewhere, wavelets have been the subject of growing excitement and interest over the past several years. Unfortunately, most books on wavelets are accessible primarily to research mathematicians. Discovering Wavelets presents basic and advanced concepts of wavelets in a way that is accessible to anyone with only a fundamental knowledge of linear algebra. The basic concepts of wavelet theory are introduced in the context of an explanation of how the FBI uses wavelets to compress fingerprint images. Wavelet theory is further developed in the setting of function spaces. The book then moves on to present more advanced topics such as filters, multiresolution analysis, Daubechies' wavelets, and further applications. The book concludes with a series of projects and problems that introduce advanced topics and offer starting points for research. Sample projects that demonstrate real wavelet applications include image compression, a wavelet-based search engine, processing with Daubechies' wavelets, and more. Among the special features of Discovering Wavelets are: * Real-life, hands-on examples that involve actual wavelet applications * A companion Web site containing Pixel Images software and Maple files to be used with the projects in the book * Challenging problems that reinforce and expand on the ideas being developed * An appendix containing the linear algebra needed to understand wavelets as presented in the book

Author Biography

EDWARD ABOUFADEL, PhD, and STEVEN SCHLICKER, PhD, are Associate Professors of Mathematics at Grand Valley State University in Allendale, Michigan.

Table of Contents

Preface v
Acknowledgments ix
Wavelets, Fingerprints, and Image Processing
1(22)
Problems of the Digital Age
1(1)
Digitizing Fingerprint Images
2(2)
Signals
4(1)
The Haar Wavelet Family
5(4)
Processing Signals
9(3)
Thresholding and Compression of Data
12(6)
The FBI Wavelet/Scalar Quantization Standard
18(5)
Wavelets and Orthogonal Decompositions
23(20)
A Lego World
23(3)
The Wavelet Sons
26(2)
Sibling Rivalry: Two Bases for Vn
28(4)
Averaging and Differencing
32(3)
Projecting Functions Onto Wavelet Spaces
35(2)
Function Processing and Image Boxes
37(4)
A Summary of Two Approaches to Wavelets
41(2)
Multiresolutions, Cascades, and Filters
43(40)
Extending the Haar Wavelets to the Real Line
43(2)
Other Elementary Wavelet Families
45(4)
Multiresolution Analysis
49(6)
The Haar Scaling Function Rediscovered
55(7)
Relationships Between the Mother and Father Wavelets
62(4)
Daubechies Wavelets
66(4)
High and Low Pass Filters
70(7)
More Problems of the Digital Age: Compact Discs
77(6)
Sample Projects
83(10)
Introduction: Overview of Projects
83(1)
Linear Algebra Project: Image Processing and Compression
84(2)
A Wavelet-Based Search Engine
86(2)
B-Splines
88(1)
Processing with the D4 Wavelets
89(2)
Daubechies Wavelets with Six Refinement Coefficients
91(2)
Appendix A Vector Spaces and Inner Product Spaces 93(14)
A.1 Vector Spaces
93(4)
A.2 Subspaces
97(1)
A.3 Inner Product Spaces
98(3)
A.4 The Orthogonal Decomposition Theorem
101(6)
Appendix B Maple Routines 107(6)
B.1 Matrix Generator
107(1)
B.2 Processing Sampled Data
108(1)
B.3 Projections onto Wavelet Spaces
109(1)
B.4 The Cascade Algorithm
110(1)
B.5 Processing an Image from Pixel Images
111(2)
Appendix C Answers to Selected Problems 113(4)
Appendix D Glossary of Symbols 117(2)
References 119(4)
Index 123

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