1、Digital Image Processing Third Edition Rafael C. Gonzalez University of Tennessee Richard E. Woods NledData Interactive Pearson International Edition prepared by Pearson Education PEARSON Prentice Hall j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j j
2、j To Samantha and To Janice, David, and Jonathan .,- / Contenls 1 Preface 15 Acknowledgments- 19 The Book Web Site 20 About the Authors 21 Introduction 23 1.1 What Is Digital Image Processing? 23 1.2 The Origins of Digital Image Processing 25 1.3 Examples of Fields that Use Digital Image Processing
3、29 1.3.1 Gamma-Ray Imaging 30 1.3.2 X-Ray Imaging 31 1.3.3 Imaging in the Ultraviolet Band 33 1.3.4 Imaging in the Visible and Infrared Bands 34 1.3.5 Imaging in the Microwave Band 40 1.3.6 Imaging in the Radio Band 42 1.3.7 Examples in which Other Imaging Modalities Are Used 42 1.4 Fundamental Step
4、s in Digital Image Processing 47 1.5 Components of an Image Processirig System 50 Summary 53 References and Further Reading 53 2 Digital Image Fundamentals 57 2.1 Elements of Visual Perception 58 2.1.1 Structure of the Human Eye 58 2.1.2 Image Formation in the Eye 60 2.1.3 Brightness Adaptation and
5、Discrimination 61 2.2 Light and the Electromagnetic Spectrum 65 2.3 Image Sensing and Acquisition 68 2.3.1 Image Acquisition Using a Single Sensor 70 2.3.2 Image Acquisition Using Sensor Strips 70 2.3.3 Image Acquisition Using Sensor Arrays 72 2.3.4 A Simple Image Formation Model 72 2.4 Image Sampli
6、ng and Quantization 74 2.4.1 Basic Concepts in Sampling and Quantization 74 2.4.2 Representing Digital Images 77 2.4.3 Spatial and Intensity Resolution 81 2.4.4 Image Interpolation 87 5 / 6 Contents 2.5 Some Basic Relationships between Pixels 90 2.5.1 Neighbors of a Pixel 90 2.5.2 Adjacency, Connect
7、ivity, Regions, and Boundaries 90 2.5.3 Distance Measures 93 2.6 An Introduction to the Mathematical Tools Used in Digital Image Processing 94 3 2.6.1 Array versus Matrix Operations 94 2.6.2 Linear versus Nonlinear Operations 95 . 2.6.3 Arithmetic Operations 96 2.6.4 Set and Logical Operations 102 2
8、.6.5 Spatial Operations 107 2.6.6 Vector and Matrix Operations 114 2.6.7 Image Transforms 115 2.6.8 Probabilistic Methods 118 Summary 120 References and Further Reading 120 Problems 121 Intensity Transformations and Spatial Filtering 126 3.1 Background 127 3.1.1 The Basics of Intensity Transformatio
9、ns and Spatial Filtering 127 3.1.2 About the Examples in This Chapter 129 3.2 Some Basic Intensity Transformation Functions 129 3.2.1 Image Negatives 130 3.2.2 Log Transformations 131 3.2.3 Power-Law (Gamma) Transformations 132 3.2.4 Piecewise-Linear Transformation Functions 137 3.3 Histogram Proces
10、sing 142 3.3.1 Histogram Equalization 144 3.3.2 Histogram Matching (Specification) 150 3.3.3 Local Histogram Processing 161 3.3.4 Using Histogram Statistics for Image Enhancement 161 3.4 Fundamentals of Spatial Filtering 166 3.4.1 The Mechanics of Spatial Filtering 167 3.4.2 Spatial Correlation and
11、Convolution 168 3.4.3 Vector Representation of Linear Filtering 172 3.4.4 Generating Spatial Filter Masks 173 3.5 Smoothing Spatial Filters 174 3.5.1 Smoothing Linear Filters 174 3.5.2 Order-Statistic (Nonlinear) Filters 178 3.6 Sharpening Spatial Filters 179 3.6.1 Foundation 180 3.6.2 Using the Sec
12、ond Derivative for Image Sharpening-The Laplacian 182 3.6.3 Unsharp Masking and Highboost Filtering 184 3.6.4 Using First-Order Derivatives for (Nonlinear) Image Sharpening-The Gradient 187 3.7 Combining Spatial Enhancement Methods 191 3.8 Using Fuzzy Techniques for Intensity Transformations and Spa
13、tial Filtering 195 4 3.B.1 Introduction 195 3.B.2 Principles of fuzzy Set Theory 196 3.8.3 Using Fuzzy Sets 200 3.8.4 Using Fuzzy Sets for Intensity Transformations 208 3.B.5 Using Fuzzy Sets for Spatial Filtering 211 Summary 214 References and Further Reading 214 Problems 215 Filtering in the Frequ
14、ency Domain 221. 4.1 Background 222 4.1.1 A Brief History of the Fourier Series and Transform 222 4.1.2 About the Examples in this Chapter 223 4.2 Preliminary Concepts 224 4.2.1 Complex Numbers 224 4.2.2 Fourier Series 225 4.2.3 Impulses and Their Sifting Property 225 4.2.4 The Fourier Transform of
15、Functions of One Continuous Variable 227 4.2.5 Convolution 231 4.3 Sampling and the Fourier Transform of Sampled Functions 233 4.3.1 Sampling 233 4.3.2 The Fourier Transform of Sampled Functions 234 4.3.3 The Sampling Theorem 235 4.3.4 Aliasing 239 4.3.5 Function Reconstruction (Recovery) from Sampl
16、ed Data 241 4.4 The Discrete Fourier Transform (DFT) of One Variable 242 4.4.1 Obtaining the OFT from the Continuous Transform of a Sampled Function 243 4.4.2 Relationship Between the Sampling and Frequency Intervals 245 4.5 Extension to Functions of Two Variables 247 4.5.1 The 2-0 Impulse and Its Sifting Property 247 4.5.2 The 2-0 Continuous Fourier Transform Pair 248 4.5.3 Two-Dimensional Sampling and the 2-0 Sampling Theorem 249 4.5.4 Aliasing in Images 250 4.5.5 The 2-0 Discrete Fourier Transform and Its Inverse 257 Contents 7
