Preface
Acknowledgments
The Book Web Site
About the Authors
1 Introduction
1.1 What Is Digital Image Processing?
1.2 The Origins of Digital Image Processing
1.3 Examples of Fields that Use Digital Image Processing
1.4 Fundamental Steps in Digital Image Processing
1.5 Components of an Image Processing System
Summary
References and Further Reading
2 Digital Image Fundamentals
2.1 Elements of Visual Perception
2.2 Light and the Electromagnetic Spectrum
2.3 Image Sensing and Acquisition
2.4 Image Sampling and Quantization
2.5 Some Basic Relationships between Pixels
2.6 An Introduction to the Mathematical Tools Used in Digital Image Processing
Summary
References and Further Reading
Problems
3 Intensity Transformations and Spatial Filtering
3.1 Background
3.2 Some Basic Intensity Transformation Functions
3.3 Histogram Processing
3.4 Fundamentals of Spatial Filtering
3.5 Smoothing Spatial Filters
3.6 Sharpening Spatial Filters
3.7 Combining Spatial Enhancement Methods
3.8 Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering
Summary
References and Further Reading
Problems
4 Filtering in the Frequency Domain
4.1 Background
4.2 Preliminary Concepts
4.3 Sampling and the Fourier Transform of Sampled Functions
4.4 The Discrete Fourier Transform (DFT) Of One Variable
4.5 Extension to Functions of Two Variables
4.6 Some Properties of the 2-D Discrete Fourier Transform
4.7 The Basics of Filtering in the Frequency Domain
4.8 Image Smoothing Using Frequency Domain Filters
4.9 I-mage Sharpening Using Frequency Domain Filters
4.10 Selective Filtering
4.11 Implementation
Summary
References and Further Reading
Problems
5 Image Restoration and Reconstruction
5.1 A Model of the Image Degradation/Restoration Process
5.2 Noise Models 335
5.3 Restoration in the Presence of Noiseonly--Spatial Filtering
5.4 Periodic Noise Reduction by Frequency Domain Filtering
5.5 Linear, Position-Invariant Degradations
5.6 Estimating the Degradation Function
5.7 Inverse Filtering
5.8 Minimum Mean Square Error (Wiener) Filtering
5.9 Constrained Least Squares Filtering
5.10 Geometric Mean Filter 383
5.11 Image Reconstruction from Projections
Summary
References and Further Reading
Problems
6 Color Image Processing
6.1 Color Fundamentals
6.2 Color Models
6.3 Pseudocolor Image Processing
6.4 Basics of Full-Color Image Processing
6.5 Color Transformations
6.6 Smoothing and Sharpening
6.7 Image Segmentation Based on Color
6.8 Noise in Color Images
6.9 Color Image Compression
Summary
References and Further Reading
Problems
7 Wavelets and Multiresolution Processing
7.1 Background
7.2 Multiresolution Expansions
7.3 Wavelet Transforms in One Dimension
7.4 The Fast Wavelet Transform
7.5 Wavelet Transforms in Two Dimensions
7.6 Wavelet Packets
Summary
References and Further Reading
Problems
8 Image Compression
8.1 Fundamentals
8.2 Some Basic Compression Methods
8.3 Digital Image Watermarking
Summary
References and Further Reading
Problems
9 Morphological Image Processing
9.1 Preliminaries
9.2 Erosion and Dilation
9.3 Opening and Closing
9.4 The Hit-or-Miss Transformation
9.5 Some Basic Morphological Algorithms
9.6 Gray-Scale Morpholog
Summary
References and Further Reading
Problems
10 Image Segmentation
10.1 Fundamentals 712
10.2 Point, Line, and Edge Detection
10.3 Thresholding
10.4 Region-Based Segmentation
10.5 Segmentation 10sing Morphological Watersheds
10.6 The Use of Motion in Segmentation
Summary
References and Further Reading
Problems
11 Representation and Description
11.1 Representation
11.2 Boundary Descriptors
11.3 Regional Descriptors
11.4 Use of Principal Components for Description
11.5 Relational Descriptors
Summary
References and Further Reading
Problems
12 Object Recognition
12.1 Patterns and Pattern Classes
12.2 Recognition Based on Decision-Theoretic Methods
12.3 Structural Methods
Summary
References and Further Reading
Problems
Appendix A
Bibliography
Index