Digital Image Processing

von: Bernd Jähne

Springer-Verlag, 2005

ISBN: 9783540275633 , 608 Seiten

6. Auflage

Format: PDF, OL

Kopierschutz: Wasserzeichen

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Mehr zum Inhalt

Digital Image Processing


 

Preface

5

Contents

9

Part I Foundation

14

1 Applications and Tools

16

1.1 A Tool for Science and Technique

16

1.2 Examples of Applications

17

1.3 Hierarchy of Image Processing Operations

28

1.4 Image Processing and Computer Graphics

30

1.5 Cross-disciplinary Nature of Image Processing

30

1.6 Human and Computer Vision

31

1.7 Components of an Image Processing System

34

1.8 Exercises

39

1.9 Further Readings

41

2 Image Representation

44

2.1 Introduction

44

2.2 Spatial Representation of Digital Images

44

2.3 Wave Number Space and Fourier Transform

54

2.4 Discrete Unitary Transforms

76

2.5 Fast Algorithms for Unitary Transforms

80

2.6 Exercises

90

2.7 Further Readings

93

3 Random Variables and Fields

94

3.1 Introduction

94

3.2 Random Variables

96

3.3 Multiple Random Variables

100

3.4 Probability Density Functions

104

3.5 Stochastic Processes and Random Fields

111

3.6 Exercises

115

3.7 Further Readings

117

4 Neighborhood Operations

118

4.1 Basic Properties and Purpose

118

4.2 Linear Shift-Invariant Filters

121

4.3 Rank Value Filters

132

4.4 LSI-Filters: Further Properties

133

4.5 Recursive Filters

135

4.6 Recursive Filters

144

4.7 Further Readings

147

5 Multiscale Representation

148

5.1 Scale

148

5.2 Multigrid Representations

151

5.3 Scale Spaces

157

5.4 Exercises

165

5.5 Further Readings

166

Part II Image Formation and Preprocessing

168

6 Quantitative Visualization

170

6.1 Introduction

170

6.2 Radiometry, Photometry, Spectroscopy, and Color

172

6.3 Waves and Particles

181

6.4 Interactions of Radiation with Matter

187

6.5 Exercises

199

6.6 Further Readings

200

7 Image Formation

202

7.1 Introduction

202

7.2 World and Camera Coordinates

202

7.3 Ideal Imaging: Perspective Projection

205

7.4 Real Imaging

208

7.5 Radiometry of Imaging

214

7.6 Linear System Theory of Imaging

218

7.7 Homogeneous Coordinates

225

7.8 Exercises

227

7.9 Further Readings

228

8 3-D Imaging

230

8.1 Basics

230

8.2 Depth from Triangulation

234

8.3 Depth from Time-of-Flight

241

8.4 Depth from Phase: Interferometry

242

8.5 Shape from Shading

242

8.6 Depth from Multiple Projections: Tomography

248

8.7 Exercises

254

8.8 Further Readings

255

9 Digitization, Sampling, Quantization

256

9.1 Definition and E.ects of Digitization

256

9.2 Image Formation, Sampling, Windowing

258

9.3 Reconstruction from Samples

262

9.4 Multidimensional Sampling on Nonorthogonal Grits

264

9.5 Quantization

266

9.6 Exercises

267

9.7 Further Readings

268

10 Pixel Processing

270

10.1 Introduction

270

10.2 Homogeneous Point Operations

271

10.3 Inhomogeneous Point Operations

281

10.4 Geometric Transformations

288

10.5 Interpolation

292

10.6 Optimized Interpolation

299

10.7 Multichannel Point Operations

304

10.8 Exercises

306

10.9 Further Redings

308

Part III Feature Extraction

310

11 Averaging

312

11.1 Introduction

312

11.2 General Properties of Averaging Filters

312

11.3 Box Filter

315

11.4 Binomial Filter

319

11.5 Effcient Large-Scale Averaging

325

11.6 Nonlinear Averaging

334

11.7 Averaging in Multichannel Images

339

11.8 Exercises

341

11.9 Further Redings

343

12 Edges

344

12.1 Introduction

344

12.2 Differential Description of Signal Changes

345

12.3 General Properties of Edge Filters

348

12.4 Gradient-Based Edge Detection

351

12.5 Edge Detection by Zero Crossings

358

12.6 Optimized Edge Detection

360

12.7 Regularized Edge Detection

362

12.8 Edges in Multichannel Images

366

12.9 Exercises

368

12.10 Further Redings

370

13 Simple Neighborhoods

372

13.1 Introduction

372

13.2 Properties of Simple Neighborhoods

373

13.3 First-Order Tensor Representation

377

13.4 Local Wave Number and Phase

388

13.5 Further Tensor Representations

397

13.6 Exercises

408

13.7 Further Redings

409

14 Motion

410

14.1 Introduction

410

14.2 Basics

411

14.3 First-Order Di.erential Methods

426

14.4 Tensor Methods

431

14.5 Correlation Methods

436

14.6 Phase Method

439

14.7 Additional Methods

441

14.8 Exercises

447

14.9 Fruther Readings

447

15 Texture

448

15.1 Introduction

448

15.2 First-Order Statistics

451

15.3 Rotation and Scale Variant Texture Features

455

15.4 Exercises

459

15.5 Further Readings

459

Part IV Image Analysis

460

16 Segmentation

462

16.1 Introduction

462

16.2 Pixel-Based Segmentation

462

16.3 Edge-Based Segmentation

466

16.4 Region-Based Segmentation

467

16.5 Model-Based Segmentation

471

16.6 Exercises

474

16.7 Further Readings

475

17 Regularization and Modeling

476

17.1 Introduction

476

17.2 Continuous Modeling I: Veriational Approach

479

17.3 Continuous Modeling II: Diffusion

486

17.4 Discrete Modeling: Inverse Problems

491

17.5 Inverse Filtering

499

17.6 Further Equivalent Approaches

505

17.7 Exercises

511

17.8 Further Redings

513

18 Morphology

514

18.1 Introduction

514

18.2 Neighborhood Operations on Binary Images

514

18.3 General Properties

516

18.4 Composite Morphological Operators

519

18.5 Exercises

525

18.6 Furtheer Readings

527

19 Shape Presentation and Analysis

528

19.1 Introduction

528

19.2 Representation of Shape

528

19.3 Moment-Based Shape Features

533

19.4 Fourier Descriptors

535

19.5 Shape Parameters

541

19.6 Exercises

544

19.7 Further Readings

545

20 Classification

546

20.1 Introduction

546

20.2 Feature Space

549

20.3 Simple Classi.cation Techniques

556

20.4 Exercises

561

20.5 Further Readings

562

Part V Reference Part

564

A Reference Material

566

B Notation

590

Bibliography

598

Index

610