Description
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. 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 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
