數(shù)字圖像處理（第三版 英文版）

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
　2.5 Some Basic Relationships between Pixels
　　2.5.1 Neighbors of a Pixel
　　2.5.2 Adjacency, Connectivity, Regions, and Boundaries
　　2.5.3 Distance Measures
2.6 An Introduction to the Mathematical Tools Used in Digital Image　Processing
　　2.6.1 Array versus Matrix Operations
　　2.6.2 Linear versus Nonlinear Operations
　　2.6.3 Arithmetic Operations
　　2.6.4 Set and Logical Operations
　　2.6.5 Spatial Operations
　　2.6.6 Vector and Matrix Operations
　　2.6.7 Image Transforms
　　2.6.8 Probabilistic Methods
　　Summary
　　References and Further Reading
　　Problems
3　Intensity Transformations and Spatial Filtering
　3.1 Background
　　3.1.1 The Basics of Intensity Transformations and Spatial Filtering
　　3.1.2 About the Examples in This Chapter
　3.2 Some Basic Intensity Transformation Functions
　　3.2.1 Image Negatives
　　3.2.2 Log Transformations
　　3.2.3 Power-Law (Gamma) Transformations
　　3.2.4 Piecewise-Linear Transformation Functions
　3.3 Histogram Processing
　　3.3.1 Histogram Equalization
　　3.3.2 Histogram Matching (Specification)
　　3.3.3 Local Histogram Processing
　　3.3.4 Using Histogram Statistics for Image Enhancement
　3.4 Fundamentals of Spatial Filtering
　　3.4.1 The Mechanics of Spatial Filtering
　　3.4.2 Spatial Correlation and Convolution
　　3.4.3 Vector Representation of Linear Filtering
　　3.4.4 Generating Spatial Filter Masks
　3.5 Smoothing Spatial Filters
　　3.5.1 Smoothing Linear Filters
　　3.5.2 Order-Statistic (Nonlinear) Filters
　3.6 Sharpening Spatial Filters
　　3.6.1 Foundation
　　3.6.2 Using the Second Derivative for Image Sharpening--The Laplacian
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