Practical Image and Video Processing Using MATLAB
Wiley - IEEE (Band Nr. 1)
1. Auflage Oktober 2011
704 Seiten, Hardcover
Wiley & Sons Ltd
Kurzbeschreibung
The book provides a practical introduction to the most important topics in image and video processing using MATLAB (and its Image Processing Toolbox) as a tool to demonstrate the most important techniques and algorithms. The contents are presented in a clear, technically accurate, objective way, with just enough mathematical detail. Most of the chapters are supported by figures, examples, illustrative problems, MATLAB scripts, suggestions for further reading, bibliographical references, useful Web sites, and exercises and computer projects to extend the understanding of their contents.
Up-to-date, technically accurate coverage of essential topics in image and video processing
This is the first book to combine image and video processing with a practical MATLAB(r)-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.
The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB(r) and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation.
Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB(r).
Extra features of this book include:
* More than 30 MATLAB(r) tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB(r)
* Chapters supported by figures, examples, illustrative problems, and exercises
* Useful websites and an extensive list of bibliographical references
This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own.
LIST OF TABLES xxxix
FOREWORD xli
PREFACE xliii
ACKNOWLEDGMENTS xlix
PART I IMAGE PROCESSING
1 INTRODUCTION AND OVERVIEW 3
1.1 Motivation / 3
1.2 Basic Concepts and Terminology / 5
1.3 Examples of Typical Image Processing Operations / 6
1.4 Components of a Digital Image Processing System / 10
1.5 Machine Vision Systems / 12
1.6 Resources / 14
1.7 Problems / 18
2 IMAGE PROCESSING BASICS 21
2.1 Digital Image Representation / 21
2.2 Image File Formats / 27
2.3 Basic Terminology / 28
2.4 Overview of Image Processing Operations / 30
3 MATLAB BASICS 35
3.1 Introduction to MATLAB / 35
3.2 Basic Elements of MATLAB / 36
3.3 Programming Tools: Scripts and Functions / 38
3.4 Graphics and Visualization / 43
3.5 Tutorial 3.1: MATLAB--a Guided Tour / 44
3.6 Tutorial 3.2: MATLAB Data Structures / 46
3.7 Tutorial 3.3: Programming in MATLAB / 53
3.8 Problems / 59
4 THE IMAGE PROCESSING TOOLBOX AT A GLANCE 61
4.1 The Image Processing Toolbox: an Overview / 61
4.2 Essential Functions and Features / 62
4.3 Tutorial 4.1: MATLAB Image Processing Toolbox--a Guided Tour / 72
4.4 Tutorial 4.2: Basic Image Manipulation / 74
4.5 Problems / 80
5 IMAGE SENSING AND ACQUISITION 83
5.1 Introduction / 83
5.2 Light, Color, and Electromagnetic Spectrum / 84
5.3 Image Acquisition / 89
5.4 Image Digitization / 93
5.5 Problems / 101
6 ARITHMETIC AND LOGIC OPERATIONS 103
6.1 Arithmetic Operations: Fundamentals and Applications / 103
6.2 Logic Operations: Fundamentals and Applications / 111
6.3 Tutorial 6.1: Arithmetic Operations / 113
6.4 Tutorial 6.2: Logic Operations and Region of Interest Processing / 118
6.5 Problems / 122
7 GEOMETRIC OPERATIONS 125
7.1 Introduction / 125
7.2 Mapping and Affine Transformations / 127
7.3 Interpolation Methods / 130
7.4 Geometric Operations Using MATLAB / 132
7.5 Other Geometric Operations and Applications / 134
7.6 Tutorial 7.1: Image Cropping, Resizing, Flipping, and Rotation / 138
7.7 Tutorial 7.2: Spatial Transformations and Image Registration / 142
7.8 Problems / 149
8 GRAY-LEVEL TRANSFORMATIONS 151
8.1 Introduction / 151
8.2 Overview of Gray-level (Point) Transformations / 152
8.3 Examples of Point Transformations / 155
8.4 Specifying the Transformation Function / 161
8.5 Tutorial 8.1: Gray-level Transformations / 163
8.6 Problems / 169
9 HISTOGRAM PROCESSING 171
9.1 Image Histogram: Definition and Example / 171
9.2 Computing Image Histograms / 173
9.3 Interpreting Image Histograms / 174
9.4 Histogram Equalization / 176
9.5 Direct Histogram Specification / 181
9.6 Other Histogram Modification Techniques / 184
9.7 Tutorial 9.1: Image Histograms / 188
9.8 Tutorial 9.2: Histogram Equalization and Specification / 191
9.9 Tutorial 9.3: Other Histogram Modification Techniques / 195
9.10 Problems / 200
10 NEIGHBORHOOD PROCESSING 203
10.1 Neighborhood Processing / 203
10.2 Convolution and Correlation / 204
10.3 Image Smoothing (Low-pass Filters) / 211
10.4 Image Sharpening (High-pass Filters) / 218
10.5 Region of Interest Processing / 222
10.6 Combining Spatial Enhancement Methods / 223
10.7 Tutorial 10.1: Convolution and Correlation / 223
10.8 Tutorial 10.2: Smoothing Filters in the Spatial Domain / 225
10.9 Tutorial 10.3: Sharpening Filters in the Spatial Domain / 228
10.10 Problems / 234
11 FREQUENCY-DOMAIN FILTERING 235
11.1 Introduction / 235
11.2 Fourier Transform: the Mathematical Foundation / 237
11.3 Low-pass Filtering / 243
11.4 High-pass Filtering / 248
11.5 Tutorial 11.1: 2D Fourier Transform / 252
11.6 Tutorial 11.2: Low-pass Filters in the Frequency Domain / 254
11.7 Tutorial 11.3: High-pass Filters in the Frequency Domain / 258
11.8 Problems / 264
12 IMAGE RESTORATION 265
12.1 Modeling of the Image Degradation and Restoration Problem / 265
12.2 Noise and Noise Models / 266
12.3 Noise Reduction Using Spatial-domain Techniques / 269
12.4 Noise Reduction Using Frequency-domain Techniques / 278
12.5 Image Deblurring Techniques / 283
12.6 Tutorial 12.1: Noise Reduction Using Spatial-domain Techniques / 289
12.7 Problems / 296
13 MORPHOLOGICAL IMAGE PROCESSING 299
13.1 Introduction / 299
13.2 Fundamental Concepts and Operations / 300
13.3 Dilation and Erosion / 304
13.4 Compound Operations / 310
13.5 Morphological Filtering / 314
13.6 Basic Morphological Algorithms / 315
Components / 321
13.7 Grayscale Morphology / 322
13.8 Tutorial 13.1: Binary Morphological Image Processing / 325
13.9 Tutorial 13.2: Basic Morphological Algorithms / 330
13.10 Problems / 334
14 EDGE DETECTION 335
14.1 Formulation of the Problem / 335
14.2 Basic Concepts / 336
14.3 First-order Derivative Edge Detection / 338
14.4 Second-order Derivative Edge Detection / 343
14.5 The Canny Edge Detector / 347
14.6 Edge Linking and Boundary Detection / 348
14.7 Tutorial 14.1: Edge Detection / 354
14.8 Problems / 363
15 IMAGE SEGMENTATION 365
15.1 Introduction / 365
15.2 Intensity-based Segmentation / 367
15.3 Region-based Segmentation / 373
15.4 Watershed Segmentation / 377
15.5 Tutorial 15.1: Image Thresholding / 379
15.6 Problems / 386
16 COLOR IMAGE PROCESSING 387
16.1 The Psychophysics of Color / 387
16.2 Color Models / 396
16.3 Representation of Color Images in MATLAB / 401
16.4 Pseudocolor Image Processing / 406
16.5 Full-color Image Processing / 409
16.6 Tutorial 16.1: Pseudocolor Image Processing / 419
16.7 Tutorial 16.2: Full-color Image Processing / 420
16.8 Problems / 425
17 IMAGE COMPRESSION AND CODING 427
17.1 Introduction / 427
17.2 Basic Concepts / 428
17.3 Lossless and Lossy Compression Techniques / 432
17.4 Image Compression Standards / 435
17.5 Image Quality Measures / 438
17.6 Tutorial 17.1: Image Compression / 440
18 FEATURE EXTRACTION AND REPRESENTATION 447
18.1 Introduction / 447
18.2 Feature Vectors and Vector Spaces / 448
18.3 Binary Object Features / 450
18.4 Boundary Descriptors / 456
18.5 Histogram-based (Statistical) Features / 464
18.6 Texture Features / 466
18.7 Tutorial 18.1: Feature Extraction and Representation / 470
18.8 Problems / 474
19 VISUAL PATTERN RECOGNITION 475
19.1 Introduction / 475
19.2 Fundamentals / 476
19.3 Statistical Pattern Classification Techniques / 487
19.4 Tutorial 19.1: Pattern Classification / 491
19.5 Problems / 497
PART II VIDEO PROCESSING
20 VIDEO FUNDAMENTALS 501
20.1 Basic Concepts and Terminology / 501
20.2 Monochrome Analog Video / 507
20.3 Color in Video / 510
20.4 Analog Video Standards / 512
20.5 Digital Video Basics / 514
20.6 Analog-to-Digital Conversion / 517
20.7 Color Representation and Chroma Subsampling / 520
20.8 Digital Video Formats and Standards / 521
20.9 Video Compression Techniques and Standards / 524
20.10 Video Processing in MATLAB / 526
20.11 Tutorial 20.1: Basic Digital Video Manipulation in MATLAB / 528
20.12 Tutorial 20.2: Working with YUV Video Data / 534
20.13 Problems / 539
21 VIDEO SAMPLING RATE AND STANDARDS CONVERSION 541
21.1 Video Sampling / 541
21.2 Sampling Rate Conversion / 542
21.3 Standards Conversion / 543
21.4 Tutorial 21.1: Line Down-Conversion / 548
21.5 Tutorial 21.2: Deinterlacing / 550
21.6 Tutorial 21.3: NTSC to PAL Conversion / 556
21.7 Tutorial 21.4: 3:2 Pull-Down / 557
21.8 Problems / 559
22 DIGITAL VIDEO PROCESSING TECHNIQUES AND APPLICATIONS 561
22.1 Fundamentals of Motion Estimation and Motion Compensation / 561
22.2 General Methodologies in Motion Estimation / 564
22.3 Motion Estimation Algorithms / 568
22.4 Video Enhancement and Noise Reduction / 573
22.5 Case Study: Object Segmentation and Tracking in the Presence of Complex Background / 576
22.6 Tutorial 22.1: Block-based Motion Estimation / 579
22.7 Tutorial 22.2: Intraframe and Interframe Filtering Techniques / 585
22.8 Problems / 589
Appendix A: HUMAN VISUAL PERCEPTION 591
A.1 Introduction / 591
A.2 The Human Eye / 592
A.3 Characteristics of Human Vision / 596
A.4 Implications and Applications of Knowledge about the Human Visual System / 609
Appendix B: GUI DEVELOPMENT 611
B.1 Introduction / 611
B.2 GUI File Structure / 611
B.3 Passing System Control / 613
B.4 The UserData Object / 615
B.5 A Working GUI Demo / 616
B.6 Concluding Remarks / 618
REFERENCES 619
INDEX 627
