Practical image and video processing using MATLAB

"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 wa...

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Detalles Bibliográficos
Otros Autores:	Marques, Oge, author (author)
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Hoboken, New Jersey : Wiley-IEEE Press 2011.
Edición:	1st edition
Materias:	MATLAB. Image processing > Mathematics. Image processing > Digital techniques.
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628014606719

Tabla de Contenidos:

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
2.1.1 Binary (1-Bit) Images / 23
2.1.2 Gray-Level (8-Bit) Images / 24
2.1.3 Color Images / 25
2.1.4 Compression / 26
2.2 Image File Formats / 27
2.3 Basic Terminology / 28
2.4 Overview of Image Processing Operations / 30
2.4.1 Global (Point) Operations / 31
2.4.2 Neighborhood-Oriented Operations / 31
2.4.3 Operations Combining Multiple Images / 32
2.4.4 Operations in a Transform Domain / 32
3 MATLAB BASICS 35
3.1 Introduction to MATLAB / 35
3.2 Basic Elements of MATLAB / 36
3.2.1 Working Environment / 36
3.2.2 Data Types / 37
3.2.3 Array and Matrix Indexing in MATLAB / 37
3.2.4 Standard Arrays / 37
3.2.5 Command-Line Operations / 38
3.3 Programming Tools: Scripts and Functions / 38
3.3.1 M-Files / 39
3.3.2 Operators / 40
3.3.3 Important Variables and Constants / 42
3.3.4 Number Representation / 42
3.3.5 Flow Control / 43
3.3.6 Code Optimization / 43
3.3.7 Input and Output / 43
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
4.2.1 Displaying Information About an Image File / 62
4.2.2 Reading an Image File / 64
4.2.3 Data Classes and Data Conversions / 65
4.2.4 Displaying the Contents of an Image / 68.
4.2.5 Exploring the Contents of an Image / 69
4.2.6 Writing the Resulting Image onto a File / 70
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
5.2.1 Light and Electromagnetic Spectrum / 84
5.2.2 Types of Images / 85
5.2.3 Light and Color Perception / 86
5.2.4 Color Encoding and Representation / 87
5.3 Image Acquisition / 89
5.3.1 Image Sensors / 89
5.3.2 Camera Optics / 92
5.4 Image Digitization / 93
5.4.1 Sampling / 95
5.4.2 Quantization / 96
5.4.3 Spatial and Gray-Level Resolution / 97
5.5 Problems / 101
6 ARITHMETIC AND LOGIC OPERATIONS 103
6.1 Arithmetic Operations: Fundamentals and Applications / 103
6.1.1 Addition / 104
6.1.2 Subtraction / 106
6.1.3 Multiplication and Division / 109
6.1.4 Combining Several Arithmetic Operations / 110
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
7.3.1 The Need for Interpolation / 130
7.3.2 A Simple Approach to Interpolation / 131
7.3.3 Zero-Order (Nearest-Neighbor) Interpolation / 132
7.3.4 First-Order (Bilinear) Interpolation / 132
7.3.5 Higher Order Interpolations / 132
7.4 Geometric Operations Using MATLAB / 132
7.4.1 Zooming, Shrinking, and Resizing / 133
7.4.2 Translation / 134
7.4.3 Rotation / 134
7.4.4 Cropping / 134
7.4.5 Flipping / 134
7.5 Other Geometric Operations and Applications / 134
7.5.1 Warping / 134
7.5.2 Nonlinear Image Transformations / 135
7.5.3 Morphing / 137
7.5.4 Seam Carving / 137
7.5.5 Image Registration / 137.
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
8.3.1 Contrast Manipulation / 155
8.3.2 Negative / 157
8.3.3 Power Law (Gamma) Transformations / 157
8.3.4 Log Transformations / 159
8.3.5 Piecewise Linear Transformations / 160
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
9.6.1 Histogram Sliding / 185
9.6.2 Histogram Stretching / 185
9.6.3 Histogram Shrinking / 186
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
10.2.1 Convolution in the One-Dimensional Domain / 204
10.2.2 Convolution in the Two-Dimensional Domain / 206
10.2.3 Correlation / 208
10.2.4 Dealing with Image Borders / 210
10.3 Image Smoothing (Low-pass Filters) / 211
10.3.1 Mean Filter / 213
10.3.2 Variations / 213
10.3.3 Gaussian Blur Filter / 215
10.3.4 Median and Other Nonlinear Filters / 216
10.4 Image Sharpening (High-pass Filters) / 218
10.4.1 The Laplacian / 219
10.4.2 Composite Laplacian Mask / 220
10.4.3 Directional Difference Filters / 220
10.4.4 Unsharp Masking / 221
10.4.5 High-Boost Filtering / 221
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
11.2.1 Basic Concepts / 237
11.2.2 The 2D Discrete Fourier Transform: Mathematical Formulation / 239
11.2.3 Summary of Properties of the Fourier Transform / 241
11.2.4 Other Mathematical Transforms / 242
11.3 Low-pass Filtering / 243
11.3.1 Ideal LPF / 244
11.3.2 Gaussian LPF / 246
11.3.3 Butterworth LPF / 246
11.4 High-pass Filtering / 248
11.4.1 Ideal HPF / 248
11.4.2 Gaussian HPF / 250
11.4.3 Butterworth HPF / 250
11.4.4 High-Frequency Emphasis / 251
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
12.2.1 Selected Noise Probability Density Functions / 267
12.2.2 Noise Estimation / 269
12.3 Noise Reduction Using Spatial-domain Techniques / 269
12.3.1 Mean Filters / 273
12.3.2 Order Statistic Filters / 275
12.3.3 Adaptive Filters / 278
12.4 Noise Reduction Using Frequency-domain Techniques / 278
12.4.1 Periodic Noise / 279
12.4.2 Bandreject Filter / 280
12.4.3 Bandpass Filter / 281
12.4.4 Notch Filter / 282
12.5 Image Deblurring Techniques / 283
12.5.1 Wiener Filtering / 286
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
13.2.1 The Structuring Element / 301.
13.3 Dilation and Erosion / 304
13.3.1 Dilation / 305
13.3.2 Erosion / 307
13.4 Compound Operations / 310
13.4.1 Opening / 310
13.4.2 Closing / 311
13.4.3 Hit-or-Miss Transform / 313
13.5 Morphological Filtering / 314
13.6 Basic Morphological Algorithms / 315
13.6.1 Boundary Extraction / 317
13.6.2 Region Filling / 319
13.6.3 Extraction and Labeling of Connected
Components / 321
13.7 Grayscale Morphology / 322
13.7.1 Dilation and Erosion / 323
13.7.2 Opening and Closing / 323
13.7.3 Top-Hat and Bottom-Hat Transformations / 325
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
14.4.1 Laplacian of Gaussian / 345
14.5 The Canny Edge Detector / 347
14.6 Edge Linking and Boundary Detection / 348
14.6.1 The Hough Transform / 349
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
15.2.1 Image Thresholding / 368
15.2.2 Global Thresholding / 369
15.2.3 The Impact of Illumination and Noise on Thresholding / 370
15.2.4 Local Thresholding / 371
15.3 Region-based Segmentation / 373
15.3.1 Region Growing / 374
15.3.2 Region Splitting and Merging / 377
15.4 Watershed Segmentation / 377
15.4.1 The Distance Transform / 378
15.5 Tutorial 15.1: Image Thresholding / 379
15.6 Problems / 386
16 COLOR IMAGE PROCESSING 387
16.1 The Psychophysics of Color / 387
16.1.1 Basic Concepts / 388
16.1.2 The CIE XYZ Chromaticity Diagram / 390
16.1.3 Perceptually Uniform Color Spaces / 393
16.1.4 ICC Profiles / 395
16.2 Color Models / 396
16.2.1 The RGB Color Model / 396
16.2.2 The CMY and CMYK Color Models / 398.
16.2.3 The HSV Color Model / 398
16.2.4 The YIQ (NTSC) Color Model / 401
16.2.5 The YCbCr Color Model / 401
16.3 Representation of Color Images in MATLAB / 401
16.3.1 RGB Images / 402
16.3.2 Indexed Images / 403
16.4 Pseudocolor Image Processing / 406
16.4.1 Intensity Slicing / 406
16.4.2 Gray Level to Color Transformations / 407
16.4.3 Pseudocoloring in the Frequency Domain / 408
16.5 Full-color Image Processing / 409
16.5.1 Color Transformations / 410
16.5.2 Histogram Processing / 412
16.5.3 Color Image Smoothing and Sharpening / 412
16.5.4 Color Noise Reduction / 414
16.5.5 Color-Based Image Segmentation / 414
16.5.6 Color Edge Detection / 417
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
17.2.1 Redundancy / 428
17.2.2 Image Encoding and Decoding Model / 431
17.3 Lossless and Lossy Compression Techniques / 432
17.3.1 Lossless Compression Techniques / 432
17.3.2 Lossy Compression Techniques / 433
17.4 Image Compression Standards / 435
17.4.1 Binary Image Compression Standards / 435
17.4.2 Continuous Tone Still Image Compression Standards / 435
17.4.3 JPEG / 436
17.4.4 JPEG 2000 / 437
17.4.5 JPEG-LS / 437
17.5 Image Quality Measures / 438
17.5.1 Subjective Quality Measurement / 438
17.5.2 Objective Quality Measurement / 439
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
18.2.1 Invariance and Robustness / 449
18.3 Binary Object Features / 450
18.3.1 Area / 450
18.3.2 Centroid / 450
18.3.3 Axis of Least Second Moment / 451
18.3.4 Projections / 451
18.3.5 Euler Number / 452
18.3.6 Perimeter / 453
18.3.7 Thinness Ratio / 453
18.3.8 Eccentricity / 454.
18.3.9 Aspect Ratio / 454
18.3.10 Moments / 455
18.4 Boundary Descriptors / 456
18.4.1 Chain Code, Freeman Code, and Shape Number / 459
18.4.2 Signatures / 461
18.4.3 Fourier Descriptors / 462
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
19.2.1 Design and Implementation of a Visual Pattern Classifier / 476
19.2.2 Patterns and Pattern Classes / 478
19.2.3 Data Preprocessing / 479
19.2.4 Training and Test Sets / 480
19.2.5 Confusion Matrix / 480
19.2.6 System Errors / 481
19.2.7 Hit Rates, False Alarm Rates, and ROC Curves / 481
19.2.8 Precision and Recall / 482
19.2.9 Distance and Similarity Measures / 485
19.3 Statistical Pattern Classification Techniques / 487
19.3.1 Minimum Distance Classifier / 488
19.3.2 k-Nearest Neighbors Classifier / 490
19.3.3 Bayesian Classifier / 490
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
20.2.1 Analog Video Raster / 507
20.2.2 Blanking Intervals / 508
20.2.3 Synchronization Signals / 509
20.2.4 Spectral Content of Composite Monochrome Analog Video / 509
20.3 Color in Video / 510
20.4 Analog Video Standards / 512
20.4.1 NTSC / 513
20.4.2 PAL / 513
20.4.3 SECAM / 514
20.4.4 HDTV / 514
20.5 Digital Video Basics / 514
20.5.1 Advantages of Digital Video / 515
20.5.2 Parameters of a Digital Video Sequence / 516
20.5.3 The Audio Component / 517
20.6 Analog-to-Digital Conversion / 517
20.7 Color Representation and Chroma Subsampling / 520
20.8 Digital Video Formats and Standards / 521
20.8.1 The Rec. 601 Digital Video Format / 522
20.8.2 The Common Intermediate Format / 523.
20.8.3 The Source Intermediate Format / 524
20.9 Video Compression Techniques and Standards / 524
20.9.1 Video Compression Standards, Codecs, and Containers / 525
20.10 Video Processing in MATLAB / 526
20.10.1 Reading Video Files / 527
20.10.2 Processing Video Files / 527
20.10.3 Playing Video Files / 527
20.10.4 Writing Video Files / 528
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
21.3.1 Deinterlacing / 543
21.3.2 Conversion between PAL and NTSC Signals / 545
21.3.3 Color Space Conversion / 545
21.3.4 Aspect Ratio Conversion / 546
21.3.5 3:2 Pull-Down / 547
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
22.2.1 Motion Representation / 566
22.2.2 Motion Estimation Criteria / 567
22.2.3 Optimization Methods / 567
22.3 Motion Estimation Algorithms / 568
22.3.1 Exhaustive Search Block Matching Algorithm / 568
22.3.2 Fast Algorithms / 570
22.3.3 Hierarchical Block Matching Algorithm / 571
22.3.4 Phase Correlation Method / 573
22.4 Video Enhancement and Noise Reduction / 573
22.4.1 Noise Reduction in Video / 574
22.4.2 Interframe Filtering Techniques / 575
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.3.1 Resolution, Viewing Distance, and Viewing Angle / 596
A.3.2 Detail and Sharpness Perception / 598
A.3.3 Optical Transfer Function and Modulation Transfer Function / 599
A.3.4 Brightness Perception / 600
A.3.5 Contrast Ratio and Contrast Sensitivity Function / 603
A.3.6 Perception of Motion / 605
A.3.7 Spatiotemporal Resolution and Frequency Response / 606
A.3.8 Masking / 608
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.

Practical image and video processing using MATLAB

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