About the Book
A newly updated and revised edition of the classic introduction to digital image processing The Fourth Edition of Digital Image Processing provides a complete introduction to the field and includes new information that updates the state of the art. The text offers coverage of new topics and includes interactive computer display imaging examples and computer programming exercises that illustrate the theoretical content of the book. These exercises can be implemented using the Programmer's Imaging Kernel System (PIKS) application program interface included on the accompanying CD.
Suitable as a textbook for students or as a reference for practitioners, this new edition provides a comprehensive treatment of these vital topics:
Characterization of continuous images
Image sampling and quantization techniques
Two-dimensional signal processing techniques
Image enhancement and restoration techniques
Image analysis techniques
Software implementation of image processing applications
In addition, the bundled CD includes:
A Solaris operating system executable version of the PIKS Scientific API
A Windows operating system executable version of PIKS Scientific
A Windows executable version of PIKSTool, a graphical user interface method of executing many of the PIKS Scientic operators without program compilation
A PDF file format version of the PIKS Scientific C programmer's reference manual
C program source demonstration programs
A digital image database of most of the source images used in the book plus many others widely used in the literature
Table of Contents:
Preface xiii
Acknowledgments xvii
PART 1 CONTINUOUS IMAGE CHARACTERIZATION 1
1 Continuous Image Mathematical Characterization 3
1.1 Image Representation, 3
1.2 Two-Dimensional Systems, 5
1.3 Two-Dimensional Fourier Transform, 10
1.4 Image Stochastic Characterization, 14
2 Psychophysical Vision Properties 23
2.1 Light Perception, 23
2.2 Eye Physiology, 26
2.3 Visual Phenomena, 29
2.4 Monochrome Vision Model, 33
2.5 Color Vision Model, 39
3 Photometry and Colorimetry 45
3.1 Photometry, 45
3.2 Color Matching, 49
3.3 Colorimetry Concepts, 54
3.4 Tristimulus Value Transformation, 61
3.5 Color Spaces, 63
PART 2 DIGITAL IMAGE CHARACTERIZATION 89
4 Image Sampling and Reconstruction 91
4.1 Image Sampling and Reconstruction Concepts, 91
4.2 Monochrome Image Sampling Systems, 99
4.3 Monochrome Image Reconstruction Systems, 110
4.4 Color Image Sampling Systems, 119
5 Image Quantization 127
5.1 Scalar Quantization, 127
5.2 Processing Quantized Variables, 133
5.3 Monochrome and Color Image Quantization, 136
PART 3 DISCRETE TWO-DIMENSIONAL PROCESSING 145
6 Discrete Image Mathematical Characterization 147
6.1 Vector-Space Image Representation, 147
6.2 Generalized Two-Dimensional Linear Operator, 149
6.3 Image Statistical Characterization, 153
6.4 Image Probability Density Models, 158
6.5 Linear Operator Statistical Representation, 162
7 Superposition and Convolution 165
7.1 Finite-Area Superposition and Convolution, 165
7.2 Sampled Image Superposition and Convolution, 174
7.3 Circulant Superposition and Convolution, 181
7.4 Superposition and Convolution Operator Relationships, 184
8 Unitary Transforms 189
8.1 General Unitary Transforms, 189
8.2 Fourier Transform, 193
8.3 Cosine, Sine and Hartley Transforms, 199
8.4 Hadamard, Haar and Daubechies Transforms, 204
8.5 Karhunen–Loeve Transform, 211
9 Linear Processing Techniques 217
9.1 Transform Domain Processing, 217
9.2 Transform Domain Superposition, 220
9.3 Fast Fourier Transform Convolution, 225
9.4 Fourier Transform Filtering, 233
9.5 Small Generating Kernel Convolution, 241
PART 4 IMAGE IMPROVEMENT 245
10 Image Enhancement 247
10.1 Contrast Manipulation, 248
10.2 Histogram Modification, 259
10.3 Noise Cleaning, 267
10.4 Edge Crispening, 284
10.5 Color Image Enhancement, 291
10.6 Multispectral Image Enhancement, 298
11 Image Restoration Models 307
11.1 General Image Restoration Models, 307
11.2 Optical Systems Models, 310
11.3 Photographic Process Models, 314
11.4 Discrete Image Restoration Models, 322
12 Image Restoration Techniques 329
12.1 Sensor and Display Point Nonlinearity Correction, 329
12.2 Continuous Image Spatial Filtering Restoration, 335
12.3 Pseudoinverse Spatial Image Restoration, 345
12.4 SVD Pseudoinverse Spatial Image Restoration, 359
12.5 Statistical Estimation Spatial Image Restoration, 364
12.6 Constrained Image Restoration, 369
12.7 Blind Image Restoration, 373
12.8 Multi-Plane Image Restoration, 379
13 Geometrical Image Modification 387
13.1 Basic Geometrical Methods, 387
13.2 Spatial Warping, 400
13.3 Perspective Transformation, 404
13.4 Camera Imaging Model, 407
13.5 Geometrical Image Resampling, 410
PART 5 IMAGE ANALYSIS 419
14 Morphological Image Processing 421
14.1 Binary Image Connectivity, 421
14.2 Binary Image Hit or Miss Transformations, 424
14.3 Binary Image Shrinking, Thinning, Skeletonizing and Thickening, 431
14.4 Binary Image Generalized Dilation and Erosion, 442
14.5 Binary Image Close and Open Operations, 453
14.6 Gray Scale Image Morphological Operations, 455
15 Edge Detection 465
15.1 Edge, Line and Spot Models, 465
15.2 First-Order Derivative Edge Detection, 471
15.3 Second-Order Derivative Edge Detection, 492
15.4 Edge-Fitting Edge Detection, 506
15.5 Luminance Edge Detector Performance, 508
15.6 Color Edge Detection, 522
15.7 Line and Spot Detection, 529
16 Image Feature Extraction 535
16.1 Image Feature Evaluation, 535
16.2 Amplitude Features, 537
16.3 Transform Coefficient Features, 542
16.4 Texture Definition, 545
16.5 Visual Texture Discrimination, 547
16.6 Texture Features, 555
17 Image Segmentation 579
17.1 Amplitude Segmentation, 580
17.2 Clustering Segmentation, 587
17.3 Region Segmentation, 590
17.4 Boundary Segmentation, 595
17.5 Texture Segmentation, 611
17.6 Segment Labeling, 613
18 Shape Analysis 623
18.1 Topological Attributes, 623
18.2 Distance, Perimeter and Area Measurements, 625
18.3 Spatial Moments, 631
18.4 Shape Orientation Descriptors, 643
18.5 Fourier Descriptors, 645
18.6 Thinning and Skeletonizing, 647
19 Image Detection and Registration 651
19.1 Template Matching, 651
19.2 Matched Filtering of Continuous Images, 655
19.3 Matched Filtering of Discrete Images, 662
19.4 Image Registration, 664
PART 6 IMAGE PROCESSING SOFTWARE 679
20 PIKS Image Processing Software 681
20.1 PIKS Functional Overview, 681
20.2 PIKS Scientific Overview, 704
21 PIKS Image Processing Programming Exercises 715
21.1 Program Generation Exercises, 716
21.2 Image Manipulation Exercises, 717
21.3 Color Space Exercises, 718
21.4 Region-of-Interest Exercises, 720
21.5 Image Measurement Exercises, 721
21.6 Quantization Exercises, 722
21.7 Convolution Exercises, 723
21.8 Unitary Transform Exercises, 724
21.9 Linear Processing Exercises, 725
21.10 Image Enhancement Exercises, 726
21.11 Image Restoration Models Exercises, 728
21.12 Image Restoration Exercises, 729
21.13 Geometrical Image Modification Exercises, 729
21.14 Morphological Image Processing Exercises, 730
21.15 Edge Detection Exercises, 732
21.16 Image Feature Extraction Exercises, 733
21.17 Image Segmentation Exercises, 734
21.18 Shape Analysis Exercises, 735
21.19 Image Detection and Registration Exercises, 735
Appendix 1 Vector-Space Algebra Concepts 737
Appendix 2 Color Coordinate Conversion 753
Appendix 3 Image Error Measures 759
Appendix 4 PIKS Compact Disk 761
Bibliography 763
Index 769
About the Author :
WILLIAM K. PRATT, PhD, has worked in imaging technology at the University of Southern California, Vicom Systems, Sun Microsystems, and, more recently, at PixelSoft. He is the author of numerous papers in the fields of communications and signal processing, and is the holder of several patents for image coding and image processing systems. He was one of the primary developers of the Programmer's Imaging Kernel System (PIKS) utilized in this volume.
WILLIAM K. PRATT, PhD, has worked in imaging technology at the University of Southern California, Vicom Systems, Sun Microsystems, and, more recently, at PixelSoft. He is the author of numerous papers in the fields of communications and signal processing, and is the holder of several patents for image coding and image processing systems. He was one of the primary developers of the Programmer's Imaging Kernel System (PIKS) utilized in this volume.
Review :
"…one of the standard reference works in image processing." (Computing Reviews.com, June 6, 2007)
"…one of the standard reference works in image processing." (Computing Reviews.com, June 6, 2007)
"…one of the standard reference works in image processing." (Computing Reviews.com, June 6, 2007)
"…one of the standard reference works in image processing." (Computing Reviews.com, June 6, 2007)
