Oge Marques
Practical Image and Video Processing Using MATLAB (eBook, PDF)
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Oge Marques
Practical Image and Video Processing Using MATLAB (eBook, PDF)
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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¯®-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…mehr
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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¯®-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¯® 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¯®. Extra features of this book include: * More than 30 MATLAB¯® tutorials, which consist of step-by-step guides toexploring image and video processing techniques using MATLAB¯® * 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.
Produktdetails
- Produktdetails
- Verlag: John Wiley & Sons
- Seitenzahl: 704
- Erscheinungstermin: 28. Juli 2011
- Englisch
- ISBN-13: 9781118093481
- Artikelnr.: 37348278
- Verlag: John Wiley & Sons
- Seitenzahl: 704
- Erscheinungstermin: 28. Juli 2011
- Englisch
- ISBN-13: 9781118093481
- Artikelnr.: 37348278
OGE MARQUES, PHD, is Associate Professor in the Department of Computer & Electrical Engineering and Computer Science at Florida Atlantic University. He has been teaching and doing research on image and video processing for more than twenty years, in seven different countries. Dr. Marques is the coauthor of Processamento Digital de Imagens and Content-Based Image and Video Retrieval and was editor-in-chief of the Handbook of Video Databases, a comprehensive work with contributions from more than 100 world experts in the field. He is a Senior Member of both the IEEE and the ACM.
List of Figures xxi List of Tables xxxix Foreword xli Preface xliii Acknowledgments xlix Part I Image Processing 1 Introduction and Overview 3 2 Image Processing Basics 21 3 MATLAB Basics 35 4 The Image Processing Toolbox at A Glance 61 5 Image Sensing and Acquisition 83 6 Arithmetic and Logic Operations 103 7 Geometric Operations 125 8 Gray-Level Transformations 151 9 Histogram Processing 171 10 Neighborhood Processing 203 11 Frequency-Domain Filtering 235 12 Image Restoration 265 13 Morphological Image Processing 299 14 Edge Detection 335 15 Image Segmentation 365 16 Color Image Processing 387 17 Image Compression and Coding 427 18 Feature Extraction and Representation 447 19 Visual Pattern Recognition 475 Part II Video Processing 20 Video Fundamentals 501 21 Video Sampling Rate And Standards Conversion 541 22 Digital Video Processing Techniques and Applications 561 Appendix A: Human Visual Perception 591 Appendix B: GUI Development 611 References 619 Index 627
LIST OF FIGURES xxi 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
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
List of Figures xxi List of Tables xxxix Foreword xli Preface xliii Acknowledgments xlix Part I Image Processing 1 Introduction and Overview 3 2 Image Processing Basics 21 3 MATLAB Basics 35 4 The Image Processing Toolbox at A Glance 61 5 Image Sensing and Acquisition 83 6 Arithmetic and Logic Operations 103 7 Geometric Operations 125 8 Gray-Level Transformations 151 9 Histogram Processing 171 10 Neighborhood Processing 203 11 Frequency-Domain Filtering 235 12 Image Restoration 265 13 Morphological Image Processing 299 14 Edge Detection 335 15 Image Segmentation 365 16 Color Image Processing 387 17 Image Compression and Coding 427 18 Feature Extraction and Representation 447 19 Visual Pattern Recognition 475 Part II Video Processing 20 Video Fundamentals 501 21 Video Sampling Rate And Standards Conversion 541 22 Digital Video Processing Techniques and Applications 561 Appendix A: Human Visual Perception 591 Appendix B: GUI Development 611 References 619 Index 627
LIST OF FIGURES xxi 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
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