冈萨雷斯《数字图像处理》MATLAB实现

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"冈萨雷斯数字图像处理是基于MATLAB的图像处理教程，由Rafael C. Gonzalez、Richard E. Woods和Steven L. Eddins合作撰写，旨在教授读者如何利用MATLAB进行数字图像处理。该书由Pearson Education, Inc.出版，并在2004年发行。" 《数字图像处理使用MATLAB》是一本由知名专家Rafael C. Gonzalez（田纳西大学）、Richard E. Woods（MedData Interactive）以及Steven L. Eddins（The MathWorks, Inc.）共同编著的专业教材。这本书深入浅出地介绍了数字图像处理的基本概念和技术，结合了MATLAB这一强大的计算环境，使得理论知识与实践操作紧密结合。 MATLAB是一种广泛用于科学计算的交互式环境，它提供了丰富的工具箱，其中包括专门用于图像处理的函数和模块。通过使用MATLAB，学习者可以方便地执行图像的获取、显示、分析、增强、复原和压缩等一系列处理任务。书中可能涵盖了以下核心知识点： 1. 图像基本概念：包括图像类型（如灰度图像、彩色图像）、像素、分辨率、图像表示（如二值图像、索引图像和真彩色图像）等。 2. 图像操作：如图像的读取与写入、显示、缩放、平移、旋转、裁剪等基础操作。 3. 图像变换：傅立叶变换、拉普拉斯变换、离散余弦变换等在图像处理中的应用，以及它们如何帮助理解和改善图像特征。 4. 图像增强：包括直方图均衡化、对比度增强、锐化、平滑滤波等方法，以改善图像质量。 5. 图像分析：如边缘检测、角点检测、形状识别等，这些是图像理解的基础。 6. 图像分割：通过阈值选择、区域生长、水平集方法等技术将图像分割成具有特定特征的区域。 7. 图像编码与压缩：JPEG、JPEG 2000、PNG等常用图像压缩算法的工作原理和实现。 8. 应用实例：可能包括医学影像分析、机器视觉、遥感图像处理等领域的真实案例。 9. MATLAB编程实践：教授如何编写MATLAB脚本和函数，以及如何利用MATLAB图像处理工具箱来实现上述各种处理技术。通过学习这本书，读者不仅可以掌握数字图像处理的理论知识，还能获得实际操作的经验，从而能够独立进行图像处理项目并解决实际问题。对于计算机科学、电子工程、生物医学工程等领域的学生和研究人员来说，这是一本非常有价值的参考书籍。

1.4 ■ Areas of Image Processing Covered in the Book 5

The MATLAB Student Version includes a full-featured version of

MATLAB. The Student Version can be purchased at significant discounts at

university bookstores and at the MathWorks’ Web site (www.mathworks.com).

Student versions of add-on products, including the Image Processing Toolbox,

also are available.

Areas of Image Processing Covered in the Book

Every chapter in this book contains the pertinent MATLAB and IPT material

needed to implement the image processing methods discussed. When a MAT-

LAB or IPT function does not exist to implement a specific method, a new

function is developed and documented. As noted earlier, a complete listing of

every new function is included in the book. The remaining eleven chapters

cover material in the following areas.

Chapter 2: Fundamentals. This chapter covers the fundamentals of MATLAB

notation, indexing, and programming concepts. This material serves as founda-

tion for the rest of the book.

Chapter 3: Intensity Transformations and Spatial Filtering. This chapter cov-

ers in detail how to use MATLAB and IPT to implement intensity transfor-

mation functions. Linear and nonlinear spatial filters are covered and

illustrated in detail.

Chapter 4: Processing in the Frequency Domain. The material in this chapter

shows how to use IPT functions for computing the forward and inverse fast

Fourier transforms (FFTs), how to visualize the Fourier spectrum, and how to

implement filtering in the frequency domain. Shown also is a method for gen-

erating frequency domain filters from specified spatial filters.

Chapter 5: Image Restoration. Traditional linear restoration methods, such as

the Wiener filter, are covered in this chapter. Iterative, nonlinear methods,

such as the Richardson-Lucy method and maximum-likelihood estimation for

blind deconvolution, are discussed and illustrated. Geometric corrections and

image registration also are covered.

Chapter 6: Color Image Processing. This chapter deals with pseudocolor and

full-color image processing. Color models applicable to digital image process-

ing are discussed, and IPT functionality in color processing is extended via im-

plementation of additional color models. The chapter also covers applications

of color to edge detection and region segmentation.

Chapter 7: Wavelets. In its current form, IPT does not have any wavelet trans-

forms.A set of wavelet-related functions compatible with the Wavelet Toolbox

is developed in this chapter that will allow the reader to implement all the

wavelet-transform concepts discussed in the Gonzalez-Woods book.

Chapter 8: Image Compression. The toolbox does not have any data compres-

sion functions. In this chapter, we develop a set of functions that can be used

for this purpose.

1.4

6 Chapter 1 ■ Introduction

Chapter 9: Morphological Image Processing. The broad spectrum of func-

tions available in IPT for morphological image processing are explained and

illustrated in this chapter using both binary and gray-scale images.

Chapter 10: Image Segmentation. The set of IPT functions available for

image segmentation are explained and illustrated in this chapter. New func-

tions for Hough transform processing and region growing also are developed.

Chapter 11: Representation and Description. Several new functions for ob-

ject representation and description, including chain-code and polygonal repre-

sentations, are developed in this chapter. New functions are included also for

object description, including Fourier descriptors, texture, and moment invari-

ants. These functions complement an extensive set of region property func-

tions available in IPT.

Chapter 12: Object Recognition. One of the important features of this chap-

ter is the efficient implementation of functions for computing the Euclidean

and Mahalanobis distances. These functions play a central role in pattern

matching. The chapter also contains a comprehensive discussion on how to

manipulate strings of symbols in MATLAB. String manipulation and matching

are important in structural pattern recognition.

In addition to the preceding material, the book contains three appendices.

Appendix A: Contains a summary of all IPT and new image-processing func-

tions developed in the book. Relevant MATLAB function also are included.

This is a useful reference that provides a global overview of all functions in the

toolbox and the book.

Appendix B: Contains a discussion on how to implement graphical user inter-

faces (GUIs) in MATLAB. GUIs are a useful complement to the material in

the book because they simplify and make more intuitive the control of inter-

active functions.

Appendix C: New function listings are included in the body of a chapter when

a new concept is explained. Otherwise the listing is included in Appendix C.

This is true also for listings of functions that are lengthy. Deferring the listing

of some functions to this appendix was done primarily to avoid breaking the

flow of explanations in text material.

The Book Web Site

An important feature of this book is the support contained in the book Web

site. The site address is

www.prenhall.com/gonzalezwoodseddins

This site provides support to the book in the following areas:

• Downloadable M-files, including all M-files in the book

• Tutorials

1.5

1.7 ■ The MATLAB Working Environment 9

†

Use of the term online in this book refers to information, such as help files, available in a local computer

system, not on the Internet.

MATLAB uses a search path to find M-files and other MATLAB-related

files, which are organized in directories in the computer file system. Any file

run in MATLAB must reside in the current directory or in a directory that

is on the search path. By default, the files supplied with MATLAB and

MathWorks toolboxes are included in the search path. The easiest way to

see which directories are on the search path, or to add or modify a search

path, is to select Set Path from the File menu on the desktop, and then use

the Set Path dialog box. It is good practice to add any commonly used di-

rectories to the search path to avoid repeatedly having the change the cur-

rent directory.

The Command History Window contains a record of the commands a user

has entered in the Command Window, including both current and previous

MATLAB sessions. Previously entered MATLAB commands can be selected

and re-executed from the Command History Window by right-clicking on a

command or sequence of commands. This action launches a menu from which

to select various options in addition to executing the commands. This is a use-

ful feature when experimenting with various commands in a work session.

1.7.2 Using the MATLAB Editor to Create M-files

The MATLAB editor is both a text editor specialized for creating M-files and

a graphical MATLAB debugger. The editor can appear in a window by itself,

or it can be a subwindow in the desktop. M-files are denoted by the extension

.m, as in pixeldup.m. The MATLAB editor window has numerous pull-down

menus for tasks such as saving, viewing, and debugging files. Because it per-

forms some simple checks and also uses color to differentiate between various

elements of code, this text editor is recommended as the tool of choice for

writing and editing M-functions.To open the editor, type edit at the prompt in

the Command Window. Similarly, typing edit filename at the prompt opens

the M-file filename.m in an editor window, ready for editing. As noted earli-

er, the file must be in the current directory, or in a directory in the search path.

1.7.3 Getting Help

The principal way to get help online

†

is to use the MATLAB Help Browser,

opened as a separate window either by clicking on the question mark symbol

(?) on the desktop toolbar, or by typing helpbrowser at the prompt in the

Command Window. The Help Browser is a Web browser integrated into the

MATLAB desktop that displays Hypertext Markup Language (HTML) docu-

ments. The Help Browser consists of two panes, the help navigator pane, used

to find information, and the display pane, used to view the information.

Self-explanatory tabs on the navigator pane are used to perform a search.

For example, help on a specific function is obtained by selecting the Search

tab, selecting Function Name as the Search Type, and then typing in the func-

tion name in the Search for field. It is good practice to open the Help Browser

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