基本信息·出版社：电子工业出版社 ·页码：609 页 ·出版日期：2009年12月 ·ISBN：9787121096006 ·条形码：9787121096006 ·版本：第1版 ·装帧：平装 ...
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基本信息·出版社：电子工业出版社
·页码：609 页
·出版日期：2009年12月
·ISBN：9787121096006
·条形码：9787121096006
·版本：第1版
·装帧：平装
·开本：16
·正文语种：英语
·丛书名：国外电子与通信教材系列
·外文书名：Digital Image Processing Using MATLAB
内容简介 《数字图像处理(MATLAB版)(英文版)》是图像处理理论与以MATLAB为主要工具的软件实践方法相结合的第一《数字图像处理(MATLAB版)(英文版)》。特色在于重点强调如何通过开发新代码来加强软件工具。介绍MATLAB编程基础知识之后，讲述了图像处理的主干内容，包括灰度变换、线性和非线性空间滤波、频率域滤波、图像恢复与配准、彩色图像处理、小波、图像数据压缩、形态学图像处理、图像分割、区域和边界表示与描述，以及目标识别。
《数字图像处理(MATLAB版)(英文版)》可供从事信号与信息处理、计算机科学与技术、通信工程、地球物理等专业的大专院校师生学习参考。
编辑推荐 《数字图像处理(MATLAB版)(英文版)》由电子工业出版社出版。
目录 In troduction
Preview
Background
What Is Digital Image Processing?
Background on MATLAB and the Image Processing Toolbox
Areas of Image Processing Covered in the Book
The Book Web Site
Notation
The MATLAB Working Environment
The MATLAB Desktop
Using the MATLAB Editor to Create M-Files
Getting Help
Saving and Retrieving a Work Session
How References Are Organized in the Book
Summary 11
Fundamentals
Preview
Digital Image RepresentatiOn
Coordinate Convenfions
Images as Matrices
Reading Images
Displaying Images
WritingImages
Data Classes
ImageTypes
Intensity Images
Binary Images
A Note on Terminology
Converting between Data Classes and Image Types
Converting between Data Classes
Converting between Image Classes and Types
Array Indexing
VectorIndexing
Matrix Indexing
Selecting Array Dimensions
Some Important Standard Arrays
Introduction to M-Function Programming
M-Files
Operators
Flow Control
Code Optimization
Interactive I/O
A Brief Introduction to Cell Arrays and Structures
Summary
Intensity Transformations and Spatial Filtering
Preview
Background
Intensity Transformation Functions
Function imad just
Logarithmic and Contrast-Stretching Transformations
Some Utility M-Functions for Intensity Transformations
Histogram Processing and Function Plotting
Generating and Plotting Image Histograms
Histogram Equalization
Histogram Matching （Specification）
Spatial Filtering
Linear Spatial Filtering
Nonlinear Spatial Filtering
Image Processing Toolbox Standard Spatial Filters
Linear Spatial Filters
Nonlinear Spatial Filters
Summary
Frequency Domain Processing
Preview
The 2-D Discrete Fourier Transform
Computing and Visualizing the 2-D DFT in MATLAB
Filtering in the Frequency Domain
Fundamental Concepts
Basic Steps in DFT Filtering
An M-function for Filtering in the Frequency Domain
Obtaining Frequency Domain Filters from Spatial Filters
Generating Filters Directly in the Frequency Domain
Creating Meshgrid Arrays for Use in Implementing Filters
in the Frequency Domain
Lowpass Frequency Domain Filters
Wireframe and Surface Plotting
Sharpening Frequency Domain Filters
Basic Highpass Filtering
High-Frequency Emphasis Filtering
Summary
Image Restoration
Preview
A Model of the Image Degradation/Restoration Process
Noise Models
Adding Noise with Function imnoise
Generating Spatial Random Noise with a Specified
Distribution
Periodic Noise
Estimating Noise Parameters
Restoration in the Presence of Noise OnlymSpatial Filtering
Spatial Noise Filters
Adaptive Spatial Filters
Periodic Noise Reduction by Frequency Domain Filtering
Modeling the Degradation Function
Direct Inverse Filtering
Wiener Filtering
Constrained Least Squares （Regularized） Filtering
Iterative Nonlinear Restoration Using the Lucy-Richardson
Algorithm
Blind Deconvolution
Geometric Transformations and Image Registration
Geometric Spatial Transformations
Applying Spatial Transformations to Images
Image Registration
Summary
Color Image Processing
Preview
Color Image Representation in MATLAB
RGB Images
Indexed Images
IPT Functions for Manipulating RGB and Indexed Images
Converting to Other Color Spaces
NTSC Color Space
The YCbCr Color Space
The HSV Color Space
The CMY and CMYK Color Spaces
The HSI Color Space
The Basics of Color Image Processing
Color Transformations
Spatial Filtering of Color Images
Color Image Smoothing
Color Image Sharpening
Working Directly in RGB Vector Space
Color Edge Detection Using the Gradient
Image Segmentation in RGB Vector Space
Summary
Wavelets
Preview
Background
The Fast Wavelet Transform
FWTs Using the Wavelet Toolbox
FWTs without the Wavelet Toolbox
Working with Wavelet Decomposition Structures
Editing Wavelet Decomposition Coefficients without
the Wavelet Toolbox
Displaying Wavelet Decomposition Coefficients
The Inverse Fast Wavelet Transform
Wavelets in Image Processing
Summary
Image Compression
Preview
Background
Coding Redundancy
Huffman Codes
Huffman Encoding
Huffman Decoding
Interpixel Redundancy
Psychovisual Redundancy
JPEG Compression
JPEG
JPEG 2000
Summary
Morphological Image Processing
Preview
Preliminaries
Some Basic Concepts from Set Theory
Binary Images, Sets, and Logical Operators
Dilation and Erosion
Dilation
Structuring Element Decomposition
The strel Function
Erosion
……
Image Segmentation
Representation and Dexcription
Object Recognition
Appendix A Function Summary
Appendix B ICE and MATLAB Graphical User Interfaces
Appendix C M-Functions
Bibliography
Index
……
序言 Solutions to problems in the field of digital image processing generally requireextensive experimental work involving software simulation and testing with large setsof sample images Although algorithm development typically is based on theoreticalunderpinnings, the actual implementation of these algorithms almost always requiresparameter estimation and, frequently, algorithm revision and comparison of candidatesolutions. Thus, selection of a flexible, comprehensive, and well-documented softwaredevelopment environment is a key factor that has important implications in the cost,development time, and portability of image processing solutions In spite of its importance, surprisingly little has been written on this aspect of thefield in the form of textbook material dealing with both theoretical principles and soft-ware implementation of digital image processing concepts. This book was written forjust this purpose. Its main objective is to provide a foundation for implementing imageprocessing algorithms using modem software tools.A complementary objective was toprepare a book that is self-contained and easily readable by individuals with a basicbackground in digital image processing, mathematical analysis, and computer pro-gramming, all at a level typical of that found in a junior/senior curriculum in a techni-cal discipline. Rudimentary knowledge of MATLAB also is desirable. To achieve these objectives, we felt that two key ingredients were needed. Thefirst was to select image processing material that is representative of material cov-ered in a formal course of instruction in this field. The second was to select soft-ware tools that are well supported and documented, and which have a wide rangeof applications in the "real" world. To meet the first objective, most of the theoretical concepts in the following chapterswere selected from Digital Image Processing by Gonzalez and Woods, which has beenthe choice introductory textbook used by educators all over the world for over twodecadesThe software tools selected are from the MATLAB Image ProcessingToolbox（IPT）, which similarly occupies a position of eminence in both education and industrialapplications A basic strategy followed in the preparation of the book was to provide aseamless integration of well-established theoretical concepts and their implementationusing state-of-the-art software tools The book is organized along the same lines as Digital Image Processing. In this way,the reader has easy access to a more detailed treatment of all the image processingconcepts discussed here, as well as an up-to-date set of references for further reading.Following this approach made it possible to present theoretical material in a succinctmanner and thus we were able to maintain a focus on the software implementation as-pects of image processing problem solutions Because it works in the MATLAB com-puting environment, the Image Processing Toolbox offers some significant advantages,not only in the breadth of its computational tools, but also because it is supportedunder most operating systems in use today.
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Another way to obtain help for a specific function is by typing doe followedby the function name at the command prompt. For example, typing doe f o r matdisplays documentation for the function called format in the display pane ofthe Help Browser. This command opens the browser if it is not already open. M-functions have two types of information that can be displayed by theuser. The first is called the H1 line, which contains the function name and aone-line description. The second is a block of explanation called the Help textblock （these are discussed in detail in Section 2.10.1）. Typing help at theprompt followed by a function name displays both the H1 line and the Helptext for that function in the Command Window. Occasionally, this informationcan be more up to date than the information in the Help browser because it isextracted directly from the documentation of the M-function in question. Typ-ing lookfor followed by a keyword displays all the H1 lines that contain thatkeyword. This function is useful when looking for a particular topic withoutknowing the names of applicable functions. For example, typing look for edgeat the prompt displays all the H1 lines containing that keyword. Because theH1 line contains the function name, it then becomes possible to look at specif-ic functions using the other help methods. Typing lookfor edge -all at theprompt displays the H1 line of all functions that contain the word edge in ei-ther the H1 line or the Help text block.Words that contain the characters edgealso are detected. For example, the H1 line of a function containing the wordpolyedge in the H1 line or Help text would also be displayed.
