数字图像处理是信息技术中的一门新兴学科，它所涵盖的内容极其丰富。麦克安德鲁编著的《数字图像处理概论》涵盖了低层次图像处理（图像增强、图像恢复）和高层次图像处理（形态学、图像分割、图像表示与描述和图像压缩）的全部基础内容，全书可作为图像处理专业课程本科生双语教学教材。

《数字图像处理概论》是美国Alasdair McAndrew(麦克安德鲁)所著Introduction to Digital Image Processing with MATLAB一书的缩编版。按照我国60学时的教学要求缩编而成。

缩编后的内容充实，涵盖了低层次图像处理（图像增强、图像恢复）和高层次图像处理（形态学、图像分割、图像表示与描述和图像压缩）的全部基础内容，习题和教材内容结合紧密，便于学生巩固所学知识。同时，缩编作者对原书部分难点进行了注释，帮助读者更好地理解所学内容。

《数字图像处理概论》可作为图像处理专业课程本科生双语教学教材。

PREFACE

CHAPTER 1 Introduction

1.1 hnages and Pictures

1.2 What is Image Processing?

1.3 Image Acquisition and Samplin~

1.4 Images and Digital Images

1.5 Some Applications

1.6 Aspects of Image Processing

1.7 An hnage-Processing Task

1.8 Types of Digital Images

1.9 Image File Sizes

1.10 Image Perception

Exercises

CHAPTER 2 Images and MATLAB

2.1 Grayscale Images

2.2 RGB Images

2.3 Indexed Color Images

2.4 Data Types and Conversions

2.5 Image Files and Formats

2.6 Files in MATLAB

Exercises

CHAPTER 3 Image Display

3.1 Introduction

3.2 Basics of Image Display

3.3 The imshow Function

3.4 Bit Planes

3.5 Spatial Resolution

3.6 Quantization mad Dithering

Exercises

CHAPTER 4 Point Processing

4.1 Introduction

4.2 Arithmetic Operations

4.3 Histograms

4.4 Lookup Tables

Exerciser

CHAPTER 5 Neighborhood Processing

5.1 Introduction

5.2 Notation

5.3 Filtering in MATLAB

5.4 Frequencies : Low-and High Pass Filters

5.5 Gaussian Filters

5.6 Edge Sharpening

5.7 Nonlinear Filters

Exercises

CHAPTER 6 Image Geometry

6.1 Interpolation of Data

6.2 hnage Interpolation

6.3 General Interpolation

6.4 Enlargement by Spatial Filtering

6.5 Scaling Smaller

6.6 Rotation

Exercises

CHAPTER 7 The Fourier Transform

7.1 Introduction

7.2 The Two-Dimensional DFF

7.3 Fourier Transforms in MATLAB

7.4 Fourier Transforms of Images

7.5 Filtering in the Frequency Domain

7.6 Homomorphic Filtering

Exercises

CHAPTER 8 Image Restoration

8.1 Introduction

8.2 Noise

8.3 Cleaning Salt and Pepper Noise

8.4 Cleaning Gaussian Noise

8.5 Removal of Periodic Noise

8.6 Inverse Filtering

8.7 Wiener Filtering

Exercises

CHAPTER 9 Image Segmentation

9.1 Introduction

9.2 Thresholding

9.3 Applications of Thresholding

9.4 Choosing an Appropriate Threshold Value

9.5 Adaptive Thresholding

9.6 Edge Detection

9.7 Derivatives and Edges

9.8 Second Derivatives

9.9 The Canny Edge Detector

9.10 The Hough Transform

9.11 Implementing the Hough Transform in MATLAB

Exercises

CHAPTER 10 Mathematical Morphology

10.1 Introduction

10.2 Basic Ideas

10.3 Dilation and Erosion

10.4 Opening and Closing

Exercises

CHAPTER 11 Image Topology

11.1 Introduction

11.2 Neighbors and Adjacency

11.3 Paths and Components

11.4 Equivalence Relations

11.5 Component Labeling

11.6 Lookup Tables

11.7 Distances and Metrics

11.8 Skeletonization

Exercises

CHAPTER 12 Shapes and Boundaries

12.1 Introduction

12.2 Chain Codes and Shape Numbers

12.3 Fourier Descriptors

Exercises

CHAPTER 13 Color Processing

13.1 What is Color?

13.2 Color Models

13.3 Color Images in MATLAB

13.4 Pseudocoloring

13.5 Processing of Color Images

Exercises

CHAPTER 14 Image Coding and Compression

14.1 Lossless and Lossy Compression

14.2 Huffman Coding

14.3 Run-length Encoding

14.4 The JPEG Algorithm

Exercises

BIBLIOGRAPHY

TERMINOLOGIES USED IN THE BOOK