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數(shù)字圖像處理(第三版 英文版)

數(shù)字圖像處理(第三版 英文版)

定 價:¥79.80

作 者: (美)岡薩雷斯,(美)伍茲 著
出版社: 電子工業(yè)出版社
叢編項: 國外電子與通信教材系列
標 簽: 多媒體

ISBN: 9787121102073 出版時間: 2010-01-01 包裝: 平裝
開本: 16開 頁數(shù): 976 字數(shù):  

內(nèi)容簡介

  本書是數(shù)字圖像處理經(jīng)典著作,作者在對32個國家的134個院校和研究所的教師、學生及自學者進行廣泛調(diào)查的基礎上編寫了第三版。除保留了第二版的大部分主要內(nèi)容外,還根據(jù)收集的建議從13個方面進行了修訂,新增400多幅圖像、200多個圖表和80多道習題,同時融入了近年來本科學領域的重要發(fā)展,使本書具有相當?shù)奶厣c先進性。全書分為12章,包括緒論、數(shù)字圖像基礎、灰度變換與空間濾波、頻域濾波、圖像復原與重建、彩色圖像處理、小波及多分辨率處理、圖像壓縮、形態(tài)學圖像處理、圖像分割、表現(xiàn)與描述、目標識別。

作者簡介

  RafaelC.Gonzalez,美國田納西大學電氣和計算機工程系教授,田納西大學圖像和模式分析實驗室、機器人和計算機視覺實驗室的創(chuàng)始人,IEEE會士。研究領域為模式識別、圖像處理和機器人。其著作已在世界范圍內(nèi)500大學和研完所采用。Richard E.Woods,美國田納西大學電氣工程系獲博士學位,IEEE會員。

圖書目錄

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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