- Hardcover: 793 pages
- Publisher: Prentice Hall; 2 edition (9 Nov 2001)
- Language English
- ISBN-10: 0201180758
- ISBN-13: 978-0201180756
- Product Dimensions: 23.9 x 18.3 x 3.3 cm
- Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: 1,292,571 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Description
Product Description
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.
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.
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Customer Reviews
Most Helpful Customer Reviews
7 of 7 people found the following review helpful
Format:Hardcover
I first got my hands on the book in a graduate level class as an undergrad. I took the class as an elective. The mathematics that was learned in the book was very conducive to other subjects like digital signal processing or advanced mathematics. This book was very easy to understand and the algorithims were very simple to follow. This is the best book for someone on the beginner level into digital image processing.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
16 reviews
33 of 35 people found the following review helpful
The best comprehensive image processing textbook
10 Dec 2005
Format:Hardcover|Amazon Verified Purchase
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.
25 of 27 people found the following review helpful
A non-commonly found textbook on Digital Image Processing
3 Jun 2002
Format:Hardcover
I've been a senior researcher in Image Processing for more than 20 years, and my opinion of the book Digital Image Processing of Gonzalez and Woods, is that it is significantly superior to current books on image processing. The contents of the books are in the mainstream of work in this field, and the level of coverage is complete and written at a level that makes it an ideal textbook for seniors and first-year graduate students. The experience of the authors shows through in the way the material is presented and illustrated. The complementary web site is an outstanding teaching aid.
13 of 14 people found the following review helpful
A very good textbook
11 Mar 2002
Format:Hardcover
As a computer engineering senior with a strong interest in image processing and vision, I found this book very helpful.
The exemples are varied and interesting, the maths are easy to understand and the design is very clear. Obviously, it supposes the reader has some mathematical background, but nothing impossible for an undergraduate student.
It is also very complete: it goes from very basic image processing concepts (defining pixels, the RGB format) to more complex topics like pattern recognition and wavelet compression.
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