本书是数字图像信息处理领域的一本经典著作,是20多年来此领域*权威的教材之一。与1977年问世的本书**版相比,进行了重要修订和扩充,增加了关于小波变换、图像形态学和彩色图像处理的章节,并新增了500多幅图像和200多幅图表。全书共分12章,首先介绍了数字图像基础、空间域和频域的图像增强;然后讨论了图像复原、彩色图像处理、小波变换及多分辨率处理和图像压缩;*后讲述了形态学图像处理、图像分割、表示与描述以及目标识别等。本书侧重于对数字图像处理基本概念和方法的介绍,并为本领域的进一步学习和研究奠定了坚实的基础。全书概念清楚、深入浅出、图文并茂,并且反映了数字图像处理领域的*新发展情况。
本书主要适用于信号与信息处理、计算机科学与技术、自动化、电子科学与技术、通信工程、地球物理、生物工程、物理、化学、医学、遥感等领域的大学教师、科技工作者、研究生、大学本科高年级学生以及工程技术人员。

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
1.3.1 Gamma-Ray Imaging
1.3.2 X-ray Imaging
1.3.3 Imaging in the Ultraviolet Band
1.3.4 Imaging in the Visible and Infrarea Bands
1.3.5 Imaging in the Microwave Band
1.3.6 Imaging in the Radio Band
1.3.7 Examples in which Other Imaging Modalities Are Used
1.4 Fundamental Steps in Digital Image Processjna
1.5 Components of an Image Processing System
Summary
References ana further Reading
2 Digital Image Fundamentals
2.1 Elements of Visual Perception
2.1.1 Structure of the Human Eye
2.1.2 Image Formation in the Eye
2.1.3 Brightness Adaptation and Discrimination
2.2 Light and the Electromagnetic Spectrum
2.3 Image Sensing and Acquisition
2.3.1 Image Acquisition Using a Single Sensor
2.3.2 Image Acquisition Using Sensor Strips
2.3.3 Image Acquisition Using Sensor Arrays
2.3.4 A Simple Image Formation Model
2.4 Image Sampling and Quantization
2.4.1 Basic Concepts in Sampling and Quantization
2.4.2 Representing Digital Images
2.4.3 Spatial and Gray-Level Resolution
2.4.4 Aliasing and Moire Patterns
2.4.5 Zooming and Shrinking Digital Images
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
2.5.4 Image Operations on a Pixel Basis
2.6 Linear and Nonlinear Operations
Summary
References and Further Reading
Problems
3 Image Enhancement in the Spatial Domain
3.1 Background
3.2 Some Basic Gray Level Transformations
3.2.1 Image Negatives
3.2.2 Log Transformations
3.2.3 Power-Law 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 Enhancement
3.3.4 Use of Histogram Statistics for Image Enhancement
3.4 Enhancement Using Arithmetic/Logic Operations
3.4.1 Image Subtraction
3.4.2 Image Averaging
3.5 Basics of Spatial Filtering
3.6 Smoothing Spatial Filters
3.6.1 Smoothing Linear Filters
3.6.2 Order-Statistics Filters
3.7 Sharpening Spatial Filters
3.7.1 Foundation
3.7.2 Use of Second Derivatives for Enhancement-The Laplacian
3.7.3 Use of First Derivatives for Enhancement-The Gradient
3.8 Combining Spatial Enhancement Methods
Summary
References and Further Reading
Problems
4 Image Enhancement in the Frequency Domain
4.1 Background
……
5 Image Restoration
6 Color Image Processing
7 Wavelets and Multiresolution Processing
8 Image Compression
9 Morphgical Image Processing
10 Image Segmentation
11 Represiontation and Description
12 Object Recognition

Rafael G.Gonzalez,于佛罗里达大学电气工程系获博士学位,田纳西大学电气与计算机工程
系教授,田纳西大学图像与模式分析实验室、机器人与计算机视觉实验室的创始人及IEEE会士。冈萨雷斯博士在模式识别、图像处理和机器人领域编写或与人合著了100多篇技术文章、编了两本书并写作了5本教材,他的书已在世界500多所大学和研究所使用。