第二版：数字化图像处理与分析实战应用

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《数字图像处理与分析（第2版）》是一本以应用为导向、工程方法为核心的书籍，专为理解和开发计算机视觉及人类感知应用程序提供工具。该书由斯科特·厄姆巴赫编写，作为CRC Press和泰勒弗朗西斯集团出版的一部分，旨在填补当前尚未有一本单一文本全面定义数字图像处理所需技能的空白。本书的核心内容围绕数字图像的获取、分析和处理展开，采用逻辑渐进的方式讲解，确保读者在理解实际图像模型的同时逐步掌握复杂理论。作者强调概念性呈现，使读者能够扎实地掌握这一领域的基础，包括数字图像处理的理论基础和推动该领域进步所需的算法开发技术。新版本的特点在于丰富的彩色应用，并且特别关注彩色图像的处理。书中包含大量实践性材料，如补充练习、全新章节探讨应用案例，以及两个创新工具——计算机视觉和图像处理算法测试与分析工具（CVIP-ATAT）和CVIP特征提取与模式分类工具（CVIP-FEPC）。这两大工具使得批量处理、算法分析以及图像应用的研发成为可能。全书分为五个主要部分，覆盖了分析数字图像所需的概念和模型，以及开发面向计算机视觉和人类用户的应用程序所需的知识。此外，书中还详尽介绍了如何在CVIPtools环境中进行算法开发，使其成为快速发展的图像处理领域的理想参考资源。作者通过《数字图像处理与分析（第2版）》引导读者进入一个统一的框架，无论是在外星地形的计算机评估，还是在高清3D电影制作中，都能有效地应用所学知识。同时，它也适合专业人士和学生，不论是对图像处理初学者，还是希望进一步提升技能的工程师，都能从中获益匪浅。

Preface

Digital image processing and analysis is a eld that continues to experience rapid growth,

with applications ranging from areas such as space exploration to the entertainment indus-

try. The diversity of applications is one of the driving forces that make it such an exciting

eld to be involved in for the twenty-rst century. Digital image processing, also referred to

as computer imaging, can be dened as the acquisition and processing of visual informa-

tion by computer. This book presents a unique approach to the practice of digital image

processing, and will be of interest to those who want to learn about and use computer

imaging techniques.

Digital image processing can be divided into two primary application areas, human

vision and computer vision, with image analysis tying these two together. Although the

book focuses on image processing and analysis, the image analysis part provides the

reader with the tools necessary for developing computer vision applications such as those

discussed in Chapter 12. The automatic identication of land types in satellites images,

robotic control of a Mars rover, and the automatic classication of abnormalities in medical

images are examples of computer vision applications. Human vision applications involve

manipulation of image data for viewing by people. Examples include the development of

better compression algorithms, special effects imaging for motion pictures, and the resto-

ration of satellite images distorted by atmospheric disturbance.

Why Write a New Edition of This Book?

The rst topic is: Why a new title? The change is primarily due to denitions used in

current practice. The previous title Computer Imaging tends now to refer to PhotoShop

type applications and document imaging only. Digital Image Processing and Analysis is more

comprehensive, explanatory, and up-to-date. The subtitle, Human and Computer Vision

Applications with CVIPtools, reinforces the applications-oriented nature of the book and

fact that CVIPtools is integrated more throughout this edition.

As before, this edition of the book takes an engineering approach to digital image pro-

cessing and brings image processing and image analysis into a unied framework that pro-

vides a useful paradigm for both human and computer vision applications. Additionally,

the theoretical foundation is presented as needed in order to fully understand the mate-

rial. Although theoretical-based textbooks are available, they do not really take what I con-

sider an engineering approach. I still feel that there is a need for an application-oriented

book that brings image processing and analysis together in a unied framework, and this

book lls that gap.

For the new edition of the book I wanted to use color throughout and add more materials on

the processing of color images. Happily, the publisher agreed. I also reorganized, updated,

expanded, and added more materials that make it more useful as an applications-oriented

textbook. I added supplementary exercises, a new chapter on applications, and developed

two new major tools that allow for batch processing, the analysis of imaging algorithms,

and the overall research and development of imaging applications.

xvi Preface

The creation of the two new software tools, the Computer Vision and Image Processing

Algorithm Test and Analysis Tool (CVIP-ATAT) and the CVIP Feature Extraction and

Pattern Classication Tool (CVIP-FEPC), realizes a much more powerful development

environment. The new Windows

version of CVIPtools, which has been integrated even

more throughout the book, in conjunction with the two new development tools, creates a

valuable environment for learning about imaging as well as providing a set of reusable

tools for applications development.

Who Will Use This Book?

The book is intended for use by the academic community in teaching and research, as well

as working professionals performing research and development in the commercial sectors.

This includes all areas of digital image processing and analysis, both human and computer

vision applications. It will be useful to academics and practicing engineers, consultants, and

programmers, as well as those in the graphics elds, medical imaging professionals, multi-

media specialists, and others. The book can be used for self-study and is of interest to anyone

involved with developing imaging applications, whether they are engineers, geographers,

biologists, oceanographers, or astronomers. At the university it can be used as a textbook in

standard digital image processing and/or computer vision senior-level or graduate courses,

or may be used at any level in an applications-oriented course. One essential component

that is missing from standard theoretical textbooks is a conceptual presentation of the

material, which is fundamental for gaining a solid understanding of these complex topics.

Additionally, this book provides the theory necessary to understand the foundations of digi-

tal image processing, as well as that which is needed for new algorithm development.

The prerequisites for the book are an interest in the eld, a basic background in computers,

and a basic math background provided in an undergraduate science or engineering pro-

gram. Knowledge of the C

, C++

, or C#

programming language will be necessary for those

intending to develop algorithms at the programming level. Some background in signal and

system theory is required for those intending to gain a deep understanding of the sections on

transforms and compression. However, the book is written so that those without this back-

ground can learn to use the tools and achieve a conceptual understanding of the material.

Approach

To help motivate the reader I have taken an approach that presents topics as needed. This

approach starts by presenting a global model to help gain an understanding of the over-

all process, followed by a breakdown and explanation of each individual topic. Instead

of presenting techniques or mathematical tools when they t into a nice, neat theoretical

framework, topics are presented as they become necessary for understanding the practi-

cal imaging model under study. This approach provides the reader with the motivation to

learn about and use the tools and topics, because they see an immediate need for them. For

example, the mathematical process of convolution is introduced when it is needed for an

image zoom algorithm, and morphological operations are introduced when the ltering

Preface xvii

operations are needed after image segmentation. This approach also makes the book more

useful as a reference, or for those who may not work through the book sequentially, but

will reference a specic section as the need arises.

Organization of the Book

The book is divided into ve major sections. The rst section of the book, Introduction

to Digital Image Processing and Analysis, contains all of the basic concepts and deni-

tions necessary to understand digital image processing. The second section, Digital Image

Analysis and Computer Vision, describes image analysis and provides the tools, concepts,

and models required to analyze digital images and develop computer vision applications.

Section III, Digital Image Processing and Human Vision, discusses topics and application

areas for the processing of images for human consumption, so it starts with a chapter on

visual perception. Each chapter includes numerous references and examples for the mate-

rial presented. The material is presented in a conceptual and application-oriented manner,

so that the reader will immediately understand how each topic ts into the overall frame-

work of imaging applications development.

The programming and applications development part of the book, Section IV, Program-

ming and Application Development with CVIPtools, provides all the necessary informa-

tion required to use the CVIPtools environment for algorithm development. This section

also includes information to assist with the implementation of the programming exercises

included with each chapter. It also includes a chapter on using the new development tools

and examples of applications that have been developed in the past few years. The last sec-

tion, Appendices, contains reference material for use with CVIPtools, as well as other useful

computer imaging–related information.

Using the Book in Your Courses

The book is intended for use in both digital image processing and computer vision courses.

Both types of courses will use the introductory chapters in the rst section. After the intro-

duction, computer vision courses will concentrate on Section II, where the introductory

chapter presents a model of image analysis and concludes with the development of a pat-

tern classication algorithm for geometric objects in images. This model provides a foun-

dation for all the tools that are developed and discussed throughout the second section.

Digital image processing courses will focus on the third section, which contains an intro-

ductory chapter on human visual perception, followed by chapters on image enhance-

ment, restoration, and compression. Most image processing courses will also want to cover

Chapter 5 on image transforms. Both computer vision and image processing courses can

use the programming parts of the book, depending on the instructor’s teaching structure.

I encourage all who use the book to explore the programming exercises as they provide a

valuable learning tool for computer imaging. There are also many tutorial exercises using

CVIPtools included with each chapter, which provide hands-on experience and allow the

user to gain insight into the various algorithms and parameters. Use the following table to

outline your course.

xviii Preface

Senior Level/Graduate

Courses

Required

Chapters

Additional/Optional

Chapters/Sections

Reference

Chapters

Image Analysis

Computer Vision

Machine Vision

1, 2, 3, 4, 5.1, 5.2, 5.7, 6, 11 5.3, 5.4, 5.5, 5.6, 5.8, 12 13, Appendices

Digital Image Processing

Digital Picture Processing

Image Processing

1, 2, 3.1, 3.2, 5.1, 5.2, 5.7,

5.8, 7, 8, 9, 10

5.3, 5.4, 5.5, 5.6, 11, 12 13, Appendices

After the CVIPtools environment is installed from the CD, an image database will be in

the default images directory, which contains the images used in the book. The CVIPtools

Website, www.ee.siue.edu/CVIPtools, is a resource that has useful imaging examples,

information and links to other imaging Web sites of interest. Additionally, a Solutions

Manual with Instructor’s CD containing PowerPoint lecture slides is available from the

publisher to those adopting the book in their courses.

CVIPtools Software Development Environment

The software development environment includes an extensive set of standard C

libraries,

a skeleton program for using the C libraries called CVIPlab, a dynamically linked library

(cviptools.dll) based on the common object module (COM) interface, a GUI-based program

for the exploration of computer imaging called CVIPtools, and the two new algorithm

development and batch processing tools CVIP-ATAT and CVIP-FEPC. The CVIPlab pro-

gram and all the standard libraries are ANSI-C compatible. The new version of CVIPtools

has been developed exclusively for the Windows

operating system, but various UNIX

versions are available at the Web site (www.ee.siue.edu/CVIPtools). The CVIPtools soft-

ware, the libraries, the CVIPlab program, CVIP-ATAT, CVIP-FEPC, images used in the

textbook, and associated documentation are included on the CD.

The CVIPtools software has been used in projects funded by the National Institutes of

Health, the U.S. Department of Defense, and numerous corporations in the commercial sec-

tor. CVIPtools has been used in the medical, aerospace, printing, and manufacturing elds

in applications such as the development of a helicopter simulation, automated classication

of lumber, skin tumor evaluation and analysis, embedded image processing for print tech-

nology, the automatic classication of defects in microdisplay chips, and the analysis of

veterinary thermographic images for disease evaluation. Since it is a university-sponsored

project, it is continually being upgraded and expanded, and updates are available via the

Internet (see Appendix B). This software allows the reader to learn about imaging topics in

an interactive and exploratory manner, and to develop their own programming expertise

with the CVIPlab program and the associated laboratory exercises. With the CVIPlab pro-

gram they can link any of the already dened CVIPtools functions, ranging from general

purpose input/output and matrix functions to more advanced transform functions and

complex imaging algorithms; some of these functions are state-of-the-art algorithms since

CVIPtools is continually being improved at the Computer Vision and Image Processing

Laboratory at Southern Illinois University Edwardsville (SIUE).

Acknowledgments

I thank Southern Illinois University Edwardsville, specically the School of Engineering

and the Electrical and Computer Engineering Department, for their support in this

endeavor. I also thank all the students who have taken my imaging courses and provided

valuable feedback regarding the learning and teaching of digital image processing and

analysis.

The initial version of the CVIPtools software was developed primarily by myself and a

few graduate students: Gregory Hance, Arve Kjoelen, Kun Luo, Mark Zuke, and Yansheng

Wei; without their hard work and dedication the foundation that was built upon for this

new version would not be solid. The next major Windows

version of CVIPtools was devel-

oped primarily by myself and Iris Cheng, Xiaohe Chen, Dejun Zhang, and Huashi Ding.

Additional students who contributed were Husain Kagalwalla and Sushma Gouravaram.

The current version of CVIPtools was initially developed by Patrick Solt and Evan Bian.

The work was completed by Patrick Solt as the project manager, with Jhansi Akkineni,

Mouinika Mamidi, Pelin Guvenc, Serkan Kefel, and Hari Krishna Akkineni providing

programming support. Jhansi Akkineni served as project coordinator and helped Patrick

with management duties.

Patrick Solt deserves special credit for helping to coordinate and manage the CVIPtools

for Windows project. He dedicated a major amount of his time to the development of the

CVIPtools software, and helped us greatly in project organization and in solving many

problems. Overall, Patrick’s contributions to this project have been substantial, and his

extra efforts deserve special recognition. Jhansi Akkineni’s efforts also deserve special

recognition. Her dedication to the project and the help she provided to others working on

the project were substantial. Iris Cheng, who was the primary contributor on the original

Windows version of CVIPtools, also deserves special recognition for her continued sup-

port as a consultant on the project.

The Computer Vision and Image Processing Algorithm Test and Analysis Tool, CVIP-

ATAT, underwent many changes before its release with this book. The initial development

was provided by Sid Smith and Jeremy Wood. Geer Shaung and Evan Bian provided sub-

stantial new developments for this tool, which helped to make it more practical for its use

with CVIPtools. Further development was required to get it into its current form, which

was completed, tested, and utilized in projects by Pelin Guvenc. The Computer Vision

and Image Processing Feature Extraction and Pattern Classication Tool, CVIP-FEPC, was

created and developed by Patrick Solt, further developed by Jesse Phelps, and partially

funded by the Long Island Veterinary Specialists.

In small but important parts of CVIPtools public domain software was used, and

kudos to those who provided it: Jef Pokanzer’s pbmplus, Sam Lefer’s TIFF library, Paul

Heckbert’s Graphics Gems, the Independent JPEG Group’s software, Yuval Fisher’s fractal

code, and the Texas Agricultural Experiment Station’s code for texture features.

I’d like to thank those who contributed photographs and images: Mark Zuke, Mike

Wilson, Tony Berke, George Dean, Sara Sawyer, Sue Eder, Jeff Zuke, Bill White, the National

Oceanic and Atmospheric Administration, NASA, and MIT. H. Kipsang Choge deserves

credit for helping out with the gures, especially for Chapters 2 and 5, and I thank him

for this work. Thanks also to David, Robin, Michael, Jeanie, Jeff, Mom, Greg, Glicer, Gaby,

www.allitebooks.com

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第二版：数字化图像处理与分析实战应用

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