数字图像处理:第3版

基本信息

书名：数字图像处理 : 第3版

定价：79.8元

作者：(美)冈萨雷斯,(美)伍兹

出版社：电子工业出版社

出版日期：2010-01-01

ISBN：9787121102073

字数：1776000

页码：976

版次：1

装帧：平装

开本：16开

商品重量：0.001kg

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内容提要

目录

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 Electromagic Spectrum
　2.3 Image Sensing and Acquisition
　2.4 Image Sampling and Quantization
　2.5 Some Basic Relationshipetween Pixels
　2.6 An Introduction to the Mathematical Tools Used in Digital Image Processing
　Summary
　2.5 Some Basic Relationshipetween Pixels
　　2.5.1 Neiors 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 s
　　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 Lacian

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