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Digital Image Processing, by Rafael C Gonzalez, Paul Wintz
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For courses in Image Processing and Computer Vision. Completely self-contained--and heavily illustrated--this introduction to basic concepts and methodologies for digital image processing is written at a level that truly is suitable for seniors and first-year graduate students in almost any technical discipline. The leading textbook in its field for more than twenty years, it continues its cutting-edge focus on contemporary developments in all mainstream areas of image processing--e.g., image fundamentals, image enhancement in the spatial and frequency domains, restoration, color image processing, wavelets, image compression, morphology, segmentation, image description, and the fundamentals of object recognition. It focuses on material that is fundamental and has a broad scope of application.
- Sales Rank: #452618 in Books
- Published on: 1987-11
- Original language: English
- Number of items: 1
- Dimensions: 9.45" h x 1.10" w x 6.69" l,
- Binding: Hardcover
- 503 pages
From the Back Cover
Digital Image Processing has been the leading textbook in its field for more than 20 years. As was the case with the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992 edition by Gonzalez and Woods, the present edition was prepared with students and instructors in mind. 771e material is timely, highly readable, and illustrated with numerous examples of practical significance. All mainstream areas of image processing are covered, including a totally revised introduction and discussion of image fundamentals, image enhancement in the spatial and frequency domains, restoration, color image processing, wavelets, image compression, morphology, segmentation, and image description. Coverage concludes with a discussion of the fundamentals of object recognition.
Although the book is completely self-contained, a Companion Website (see inside front cover) provides additional support in the form of review material, answers to selected problems, laboratory project suggestions. and a score of other features. A supplementary instructor's manual is available to instructors who have adopted the book for classroom use.
New Features- New chapters on wavelets, image morphology, and color image processing.
- More than 500 new images and over 200 new line drawings and tables.
- A revision and update of all chapters, including topics such as segmentation by watersheds.
- Numerous new examples with processed images of higher resolution.
- A reorganization that allows the reader to get to the material on actual image processing much sooner than before.
- Updated image compression standards and a new section on compression using wavelets.
- A more intuitive development of traditional topics such as image transforms and image restoration.
- Updated bibliography.
About the Author
Rafael C. Gonzalez received the B.S.E.E. degree from the University of Miami in 1965 and the M.E. and Ph.D. degrees in electrical engineering from the University of Florida, Gainesville, in 1967 and 1970, respectively. He joined the Electrical and Computer Engineering Department at University of Tennessee, Knoxville (UTK) in 1970, where he became Associate Professor in 1973, Professor in 1978, and Distinguished Service Professor in 1984. He served as Chairman of the department from 1994 through 1997. He is currently a Professor Emeritus at UTK.
Gonzalez is the founder of the Image & Pattern Analysis Laboratory and the Robotics & Computer Vision Laboratory at the University of Tennessee. He also founded Perceptics Corporation in 1982 and was its president until 1992. The last three years of this period were spent under a full-time employment contract with Westinghouse Corporation, who acquired the company in 1989.
Under his direction, Perceptics became highly successful in image processing, computer vision, and laser disk storage technology. In its initial ten years, Perceptics introduced a series of innovative products, including: The world's first commercially-available computer vision system for automatically reading the license plate on moving vehicles; a series of large-scale image processing and archiving systems used by the U.S. Navy at six different manufacturing sites throughout the country to inspect the rocket motors of missiles in the Trident II Submarine Program; the market leading family of imaging boards for advanced Macintosh computers; and a line of trillion-byte laser disk products.
He is a frequent consultant to industry and government in the areas of pattern recognition, image processing, and machine learning. His academic honors for work in these fields include the 1977 UTK College of Engineering Faculty Achievement Award; the 1978 UTK Chancellor's Research Scholar Award; the 1980 Magnavox Engineering Professor Award; and the 1980 M.E. Brooks Distinguished Professor Award. In 1981 he became an IBM Professor at the University of Tennessee and in 1984 he was named a Distinguished Service Professor there. He was awarded a Distinguished Alumnus Award by the University of Miami in 1985, the Phi Kappa Phi Scholar Award in 1986, and the University of Tennessee's Nathan W. Dougherty Award for Excellence in Engineering in 1992.
Honors for industrial accomplishment include the 1987 IEEE Outstanding Engineer Award for Commercial Development in Tennessee; the 1988 Albert Rose Nat'l Award for Excellence in Commercial Image Processing; the 1989 B. Otto Wheeley Award for Excellence in Technology Transfer; the 1989 Coopers and Lybrand Entrepreneur of the Year Award; the 1992 IEEE Region 3 Outstanding Engineer Award; and the 1993 Automated Imaging Association National Award for Technology Development.
Gonzalez is author or co-author of over 100 technical articles, two edited books, and four textbooks in the fields of pattern recognition, image processing and robotics. His books are used in over 500 universities and research institutions throughout the world. He is listed in the prestigious Marquis Who's Who in America, Marquis Who's Who in Engineering, Marquis Who's Who in the World, and in 10 other national and international biographical citations. He ii the co-holder of two U.S. Patents, and has been an associate editor of the IEEE Transactions on Systems, Man and Cybernetics, and the International Journal of Computer and Information Sciences. He is a member of numerous professional and honorary societies, including Tau Beta Pi, Phi Kappa Phi, Eta Kapp Nu, and Sigma Xi. He is a Fellow of the IEEE.
Richard E. Woods earned his B.S., M.S., and Ph.D. degrees in Electrical Engineering from the University of Tennessee, Knoxville. His professional experiences range from entrepreneurial to the
Excerpt. © Reprinted by permission. All rights reserved.
When something can be read without effort,
great effort has gone into its writing.
— Enrique Jardiel Poncela
This edition is the most comprehensive revision of Digital Image Processing since the book first appeared in 1977. As the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992 edition by Gonzalez and Woods, the present edition was prepared with students and instructors in mind. Thus, the principal objectives of the book continue to be to provide an introduction to basic concepts and methodologies for digital image processing, and to develop a foundation that can be used as the basis for further study and research in this field. To achieve these objectives, we again focused on material that we believe is fundamental and has a scope of application that is not limited to the solution of specialized problems. The mathematical complexity of the book remains at a level well within the grasp of college seniors and first-year graduate students who have introductory preparation in mathematical analysis, vectors, matrices, probability, statistics, and rudimentary computer programming.
The present edition was influenced significantly by a recent market survey conducted by Prentice Hall. The major findings of this survey were:
The reorganization that resulted in this edition is our attempt at providing a reasonable degree of balance between rigor in the presentation, the findings of the market survey, and suggestions made by students, readers, and colleagues since the last edition of the book. The major changes made in the book are as follows.
Chapter 1 was rewritten completely. The main focus of the current treatment is on examples of areas that use digital image processing. While far from exhaustive, the examples shown will leave little doubt in the reader's mind regarding the breadth of application of digital image processing methodologies. Chapter 2 is totally new also. The focus of the presentation in this chapter is on how digital images are generated, and on the closely related concepts of sampling, abasing, Moire patterns, and image zooming and shrinking. The new material and the manner in which these two chapters were reorganized address, directly the first two findings in the market survey mentioned above.
Chapters 3 though 6 in the current edition cover the same concepts as Chapters 3 through 5 in the previous edition, but the scope is expanded and the presentation is totally different. In the previous edition, Chapter 3 was devote(( exclusively to image transforms. One of the major changes in the book is that image transforms are now introduced when they are needed. This allowed us to begin discussion of image processing techniques much earlier than before, further addressing the second finding of the market survey. Chapters 3 and 4 in the current edition deal with image enhancement, as opposed to a single chapter (Chapter 4) in the previous edition. The new organization of this material doe; not imply that image enhancement is more important than other areas. Rather we used it as an avenue to introduce spatial methods for image processing; (Chapter 3), as well as the Fourier transform, the frequency domain, and image filtering (Chapter 4). Our purpose for introducing these concepts in the context of image enhancement (a subject particularly appealing to beginners) was to increase the level of intuitiveness in the presentation, thus addressing partially, the third major finding in the marketing survey. This organization also gives instructors flexibility in the amount of frequency-domain material they wish to ever.
Chapter 5 also was rewritten completely in a more intuitive manner. The coverage of this topic in earlier editions of the book was based on matrix theory. Although unified and elegant, this type of presentation is difficult to follow particularly by undergraduates. The new presentation covers essentially the same ground, but the discussion does not rely on matrix theory and is much easier to understand, due in part to numerous new examples. The price paid fog this newly gained simplicity is the loss of a unified approach, in the sense the in the earlier treatment a number of restoration results could be derived from one basic formulation. On balance, however, we believe that readers (especially beginners) will find the new treatment much more appealing and easier to follow. Also, as indicated below, the old material is stored in the book Web site for easy access by individuals preferring to follow a matrix-theory formulation.
Chapter 6 dealing with color image processing is new. Interest in this area ha increased significantly in the past few years as a result of growth in the use a digital images for Internet applications. Our treatment of this topic represent) a significant expansion of the material from previous editions. Similarly Chapter 7, dealing with wavelets, is new. In addition to a number of signal processing applications, interest in this area is motivated by the need for mop sophisticated methods for image compression, a topic that in turn is motivate; by a increase in the number of images transmitted over the Internet or store; in web servers. Chapter 8 dealing with image compression was updated to in dude new compression methods and standards, but its fundamental structure remains the same as in the previous edition. Several image transforms, previous)) covered in Chapter 3 and whose principal use is compression, were moved to this chapter.
Chapter 9, dealing with image morphology, is new. It is based on a significant expansion of the material previously included as a section in the chapter on image representation and description. Chapter 10, dealing with image segmentation, has the same basic structure as before, but numerous new examples were included and a new section on segmentation by morphological watersheds was added. Chapter 11, dealing with image representation and description, was shortened slightly by the removal of the material now included in Chapter 9. New examples were added and the Hotelling transform (description by principal components), previously included in Chapter 3, was moved to this chapter. Chapter 12 dealing with object recognition was shortened by the removal of topics dealing with knowledge-based image analysis, a topic now covered in considerable detail in a number of books which we reference in Chapters 1 and 12. Experience since the last edition of Digital Image Processing indicates that the new, shortened coverage of object recognition is a logical place at which to conclude the book.
Although the book is totally self-contained, we have established a companion web site (see inside front cover) designed to provide support to users of the book. For students following a formal course of study or individuals embarked on a program of self study, the site contains a number of tutorial reviews on background material such as probability, statistics, vectors, and matrices, prepared at a basic level and written using the same notation as in the book. Detailed solutions to many of the exercises in the book also are provided. For instruction, the site contains suggested teaching outlines, classroom presentation materials, laboratory experiments, and various image databases (including most images from the book). In addition, part of the material removed from the previous edition is stored in the web site for easy download and classroom use, at the discretion of the instructor. A downloadable instructor's manual containing sample curricula, solutions to sample laboratory experiments, and solutions to all problems in the book is available to instructors who have adopted the book for classroom use.
This edition of Digital Image Processing is a reflection of the significant progress that has been made in this field in just the past decade. As is usual in a project such as this, progress continues after work on the manuscript stops. One of the reasons earlier versions of this book have been so well accepted throughout the world is their emphasis on fundamental concepts, an approach that, among other things, attempts to provide a measure of constancy in a rapidly-evolving body of knowledge. We have tried to observe that same principle in preparing this edition of the book.
R.C.G.
R.E.W.
Most helpful customer reviews
36 of 38 people found the following review helpful.
The best comprehensive image processing textbook
By calvinnme
This book is the best textbook on image processing for senior/graduate students majoring in engineering or computer science. Although a knowledge of calculus and linear algebra is presumed, it is a very accessible textbook. Chapters one and two consist of very basic background information. The concepts of linearity, pixel distance measures, spatial versus gray scale resolution, and zooming and shrinking are explained. Chapter 3 is about image inhancement in the spatial domain, and includes discussions on contrast enhancement, histogram processing and equalization, and histogram matching. The idea of filtering images via an NxN kernel mask is also introduced. Chapter 4 is about filtering in the frequency domain. The 2D Fourier transform is introduced and it is explained how filtering can take place using this transform. Chapter five discusses image restoration. This includes Weiner filtering and minimum mean square error filtering. Chapter six discusses color image processing. This chapter discusses the various color spaces - RGB, CMYK, HSI, and how the transforms mentioned up to this point in the book can be performed in color. Chapter 7 is about wavelets and multiresolution processing. This chapter is a good solid presentation of wavelets and their usage in image processing. I would suggest that anyone interested in this subject start here before they read another book, since the presentation is clearer here than in books dedicated to the subject. Chapter 8 is about image compression. Basics of information theory are discussed, and lossy as well as lossless methods of compression are discussed. As a good follow-on to the previous chapter, the role of wavelets in compression is discussed. Chapter 9 discusses morphological image processing, which is that field of image processing that relies on the systematic "fattening" and "thinning" of edges to enhance images. Chapters 10,11, and 12 are a sort of introduction to computer vision topics. Chapter 10 discusses how to segment an image. Chapter 11 is about image descriptors that quantify segmented portions of an image. Chapter 12 is about object recognition and even has a short section on statistical classifiers. This book is a joy to read, and will make the topic of image processing very clear. There are plenty of diagrams, formulas, and equations listed. There are no examples to speak of, but algorithms are clearly specified so that I don't think that the book suffers because of the lack of examples. All engineering textbooks should be this well written. I particularly recommend this book as a reference for students and practitioners of robotics, video processing, and computer vision, since there are image processing considerations in all of these fields that this book will clarify.
0 of 0 people found the following review helpful.
Four Stars
By Jesus Fuentes
Book is in excellent shape.
9 of 10 people found the following review helpful.
Simply Excellent! Fully Justifies Its Price!
By Musaad Haider
The preface of this book starts with a quote:
"When something can be read without effort, great effort has gone into its writing".
And once you start reading the book, you realize how much the book lives upto this. Everything is written clearly and importany points are stressed again and again in each topic until you become fully familiar with them. Topics are written with implementation in mind, as you can get started with writing your own code instantly.
The book makes the subject as interseting as it gets, and although some existing basic concepts of mathematics and statistics are quite helpful while reading, but you dont even have to be familiar with Digital Signal Processing to fully understand the contents.
Finally, I'd like to say that out of the few poeple that fully understand a concept, fewer have the gift to deliver their knowledge to others, and the authors of this book have that gift.
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