Description

Book Synopsis

Updated and Expanded Textbook Offers Accessible and Applications-First Introduction to Wavelet Theory for Students and Professionals

The new edition of Discrete Wavelet Transformations continues to guide readers through the abstract concepts of wavelet theory by using Dr. Van Fleet's highly practical, application-based approach, which reflects how mathematicians construct solutions to challenges outside the classroom. By introducing the Haar, orthogonal, and biorthogonal filters without the use of Fourier series, Van Fleet allows his audience to connect concepts directly to real-world applications at an earlier point than other publications in the field.

Leveraging extensive graphical displays, this self-contained volume integrates concepts from calculus and linear algebra into the constructions of wavelet transformations and their applications, including data compression, edge detection in images and denoising of signals. Conceptual understanding is rein

Table of Contents

1 Introduction: Why Wavelets? 1

2 Vectors and Matrices 15

2.1 Vectors, Inner Products, and Norms 16

Problems 21

2.2 Basic Matrix Theory 23

Problems 38

2.3 Block Matrix Arithmetic 40

Problems 48

2.4 Convolution and Filters 51

Problems 65

3 An Introduction to Digital Images 69

3.1 The Basics of Grayscale Digital Images 70

Problems 88

Computer Lab 91

3.2 Color Images and Color Spaces 91

Problems 103

Computer Lab 106

3.3 Huffman Coding 106

Problems 113

3.4 Qualitative and Quantitative Measures 114

Problems 120

Computer Labs 123

4 The Haar Wavelet Transformation 125

4.1 Constructing the Haar Wavelet Transformation 127

Problems 137

Computer Lab 140

4.2 Iterating the Process 140

Problems 146

Computer Lab 147

4.3 The Two-Dimensional Haar Wavelet Transformation 147

Problems 159

Computer Lab 161

4.4 Applications: Image Compression and Edge Detection 161

Problems 177

Computer Labs 181

5 Daubechies Wavelet Transformations 183

5.1 Daubechies Filter of Length 4 185

Problems 196

Computer Lab 203

5.2 Daubechies Filter of Length 6 203

Problems 212

Computer Lab 215

5.3 Daubechies Filters of Even Length 215

Problems 225

Computer Lab 228

6 Wavelet Shrinkage: An Application to Denoising 231

6.1 An Overview of Wavelet Shrinkage 232

Problems 237

Computer Lab 238

6.2 VisuShrink 238

Problems 245

Computer Lab 246

6.3 SureShrink 246

Problems 257

Computer Labs 260

7 Biorthogonal Wavelet Transformations 261

7.1 The (5; 3) Biorthogonal Spline Filter Pair 262

Problems 273

Computer Lab 278

7.2 The (8; 4) Biorthogonal Spline Filter Pair 278

Problems 283

Computer Lab 288

7.3 Symmetry and Boundary Effects 288

Problems 307

Computer Lab 311

7.4 Image Compression and Image Pansharpening 312

Computer Lab 320

8 Complex Numbers and Fourier Series 321

8.1 The Complex Plane and Arithmetic 322

Problems 332

8.2 Fourier Series 334

Problems 344

8.3 Filters and Convolution in the Fourier Domain 349

Problems 360

9 Filter Construction in the Fourier Domain 365

9.1 Filter Construction 366

Problems 377

9.2 Daubechies Filters 378

Problems 382

9.3 Coiflet Filters 382

Problems 395

9.4 Biorthogonal Spline Filter Pairs 400

Problems 410

Computer Lab 413

9.5 The Cohen–Daubechies–Feauveau 9/7 Filter 414

Problems 423

Computer Lab 426

10 Wavelet Packets 427

10.1 The Wavelet Packet Transform 428

Problems 435

10.2 Cost Functions and the Best Basis Algorithm 436

Problems 444

10.3 The FBI Fingerprint Compression Specification 446

Computer Lab 460

11 Lifting 461

11.1 The LeGall Wavelet Transform 462

Problems 471

Computer Lab 473

11.2 Z–Transforms and Laurent Polynomials 474

Problems 484

11.3 A General Construction of the Lifting Method 486

Problems 499

11.4 The Lifting Method – Examples 504

Problems 517

12 The JPEG2000 Image Compression Standard 525

12.1 An Overview of JPEG 526

Problems 532

12.2 The Basic JPEG2000 Algorithm 533

Problems 539

12.3 Examples 540

A Basic Statistics 547

A.1 Descriptive Statistics 547

Problems 549

A.2 Sample Spaces, Probability, and Random Variables 550

Problems 553

A.3 Continuous Distributions 553

Problems 559

A.4 Expectation 559

Problems 565

A.5 Two Special Distributions 566

Problems 568

Discrete Wavelet Transformations

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    A Hardback by Patrick J. Van Fleet

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      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 10/05/2019
      ISBN13: 9781118979273, 978-1118979273
      ISBN10: 1118979273

      Description

      Book Synopsis

      Updated and Expanded Textbook Offers Accessible and Applications-First Introduction to Wavelet Theory for Students and Professionals

      The new edition of Discrete Wavelet Transformations continues to guide readers through the abstract concepts of wavelet theory by using Dr. Van Fleet's highly practical, application-based approach, which reflects how mathematicians construct solutions to challenges outside the classroom. By introducing the Haar, orthogonal, and biorthogonal filters without the use of Fourier series, Van Fleet allows his audience to connect concepts directly to real-world applications at an earlier point than other publications in the field.

      Leveraging extensive graphical displays, this self-contained volume integrates concepts from calculus and linear algebra into the constructions of wavelet transformations and their applications, including data compression, edge detection in images and denoising of signals. Conceptual understanding is rein

      Table of Contents

      1 Introduction: Why Wavelets? 1

      2 Vectors and Matrices 15

      2.1 Vectors, Inner Products, and Norms 16

      Problems 21

      2.2 Basic Matrix Theory 23

      Problems 38

      2.3 Block Matrix Arithmetic 40

      Problems 48

      2.4 Convolution and Filters 51

      Problems 65

      3 An Introduction to Digital Images 69

      3.1 The Basics of Grayscale Digital Images 70

      Problems 88

      Computer Lab 91

      3.2 Color Images and Color Spaces 91

      Problems 103

      Computer Lab 106

      3.3 Huffman Coding 106

      Problems 113

      3.4 Qualitative and Quantitative Measures 114

      Problems 120

      Computer Labs 123

      4 The Haar Wavelet Transformation 125

      4.1 Constructing the Haar Wavelet Transformation 127

      Problems 137

      Computer Lab 140

      4.2 Iterating the Process 140

      Problems 146

      Computer Lab 147

      4.3 The Two-Dimensional Haar Wavelet Transformation 147

      Problems 159

      Computer Lab 161

      4.4 Applications: Image Compression and Edge Detection 161

      Problems 177

      Computer Labs 181

      5 Daubechies Wavelet Transformations 183

      5.1 Daubechies Filter of Length 4 185

      Problems 196

      Computer Lab 203

      5.2 Daubechies Filter of Length 6 203

      Problems 212

      Computer Lab 215

      5.3 Daubechies Filters of Even Length 215

      Problems 225

      Computer Lab 228

      6 Wavelet Shrinkage: An Application to Denoising 231

      6.1 An Overview of Wavelet Shrinkage 232

      Problems 237

      Computer Lab 238

      6.2 VisuShrink 238

      Problems 245

      Computer Lab 246

      6.3 SureShrink 246

      Problems 257

      Computer Labs 260

      7 Biorthogonal Wavelet Transformations 261

      7.1 The (5; 3) Biorthogonal Spline Filter Pair 262

      Problems 273

      Computer Lab 278

      7.2 The (8; 4) Biorthogonal Spline Filter Pair 278

      Problems 283

      Computer Lab 288

      7.3 Symmetry and Boundary Effects 288

      Problems 307

      Computer Lab 311

      7.4 Image Compression and Image Pansharpening 312

      Computer Lab 320

      8 Complex Numbers and Fourier Series 321

      8.1 The Complex Plane and Arithmetic 322

      Problems 332

      8.2 Fourier Series 334

      Problems 344

      8.3 Filters and Convolution in the Fourier Domain 349

      Problems 360

      9 Filter Construction in the Fourier Domain 365

      9.1 Filter Construction 366

      Problems 377

      9.2 Daubechies Filters 378

      Problems 382

      9.3 Coiflet Filters 382

      Problems 395

      9.4 Biorthogonal Spline Filter Pairs 400

      Problems 410

      Computer Lab 413

      9.5 The Cohen–Daubechies–Feauveau 9/7 Filter 414

      Problems 423

      Computer Lab 426

      10 Wavelet Packets 427

      10.1 The Wavelet Packet Transform 428

      Problems 435

      10.2 Cost Functions and the Best Basis Algorithm 436

      Problems 444

      10.3 The FBI Fingerprint Compression Specification 446

      Computer Lab 460

      11 Lifting 461

      11.1 The LeGall Wavelet Transform 462

      Problems 471

      Computer Lab 473

      11.2 Z–Transforms and Laurent Polynomials 474

      Problems 484

      11.3 A General Construction of the Lifting Method 486

      Problems 499

      11.4 The Lifting Method – Examples 504

      Problems 517

      12 The JPEG2000 Image Compression Standard 525

      12.1 An Overview of JPEG 526

      Problems 532

      12.2 The Basic JPEG2000 Algorithm 533

      Problems 539

      12.3 Examples 540

      A Basic Statistics 547

      A.1 Descriptive Statistics 547

      Problems 549

      A.2 Sample Spaces, Probability, and Random Variables 550

      Problems 553

      A.3 Continuous Distributions 553

      Problems 559

      A.4 Expectation 559

      Problems 565

      A.5 Two Special Distributions 566

      Problems 568

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