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Digital Image Processing (4th Edition)
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Introduce your students to image processing with the industry’s most prized text For 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. As in all earlier editions, the focus of this edition of the book is on fundamentals. The 4th Edition, which celebrates the book’s 40th anniversary, is based on an extensive survey of faculty, students, and independent readers in 150 institutions from 30 countries. Their feedback led to expanded or new coverage of topics such as deep learning and deep neural networks, including convolutional neural nets, the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering and superpixels, active contours (snakes and level sets), and exact histogram matching. Major improvements were made in reorganizing the material on image transforms into a more cohesive presentation, and in the discussion of spatial kernels and spatial filtering. Major revisions and additions were made to examples and homework exercises throughout the book. For the first time, we added MATLAB projects at the end of every chapter, and compiled support packages for you and your teacher containing, solutions, image databases, and sample code. The support materials for this title can be found at www.ImageProcessingPlace.com
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Product details
Hardcover: 1168 pages
Publisher: Pearson; 4 edition (March 30, 2017)
Language: English
ISBN-10: 9780133356724
ISBN-13: 978-0133356724
ASIN: 0133356728
Product Dimensions:
7.7 x 1.8 x 9.2 inches
Shipping Weight: 3.6 pounds (View shipping rates and policies)
Average Customer Review:
4.1 out of 5 stars
62 customer reviews
Amazon Best Sellers Rank:
#127,028 in Books (See Top 100 in Books)
This is a good introduction to image processing.The first chapters introduce the readers to the fundamentals of human vision and how the brain processes light, contrast and color. The examples are clear and understandable.As the book progresses, the subjects become more complex and mathematically-oriented. I found that I could follow up with those topics in which I had prior background, like intensity transformations, spatial filtering, filtering in the frequency domain, color image processing, image compression and image segmentation. In these topics I understood most of what they were explaining, except maybe the last pages of each chapter.When it came to chapters where I was weaker or not familiar at all, I have to admit that I was able to keep up only with the first pages of each one. More specifically: Wavelets and multithreshold processing, morphological image processing, representation, fuzzy logic and object recognition. These chapters became muddy very quickly, and I only got a general feeling about what they were explaining.Maybe someone with an electrical engineering background (myself being mechanical/software) would understand better the advanced topics.I plan to read them again once I have a practical need or use for those areas.The book does not contain code samples but it has quite a lot of practical use examples with pictures.In summary, I understood roughly 65% of the book and would recommend it to anyone who needs a better understanding of image processing.Best RegardsAri
This book is a wonderful read about image processing. Having read most of the 1st edition (yes I'm reading all of the 3rd), I can say that this 3rd edition is larger (yet not insurmountable) with more examples, explanations, mathematical development and new material. I'm currently in the chapter about frequency domain processing and must say that the previous chapter about spatial domain processing is more robust, even now including a good introduction to fuzzy logic. Anyhow, with a good background in applied math and Matlab programming, this material is easy reading for me, but should also be accessible enough for anyone with a general technical background.
I just completed a semester of Digital Image Processing where this was the course textbook. Of the myriad textbooks I have used over the years, this one is definitely at the top of my list in terms of its clarity and organization. I ended up reading at least two thirds of this textbook, and the way that the authors present the material makes it very clear in most cases. I came away with the sense that the authors expended a great deal of effort in illustrating and explaining the concepts - more so than many textbooks I have encountered, especially those at the graduate engineering level.My only criticism is that certain parts of chapters 7 and 8 seemed a bit too extensive for an introductory image processing text; however, they were still good chapters and so I don't think that it warrants a deduction of a star in my rating.I highly recommend this text if you need to take an image processing course.
Very good and comprehensive text, which could be improved with more concrete examples, algorithm pseudo-code and more extensive treatment of processing colour images. Otherwise, this book is a good introduction to image processing.
Gonzalez & Woods (3rd ed) is not only the best single reference in the field of image processing, but it is also one of the best technical books I ever read, in any field. Text and examples are clear, mathematics is at the right level to be precise, formal and understandable as well. You'll learn a lot about many things in this book.
Awesome copy!!!
I like this book. Some of the methods are a little old, but this book is great at covering the basics.
Lots of reference information. Most mathematical concepts presented in a clear manner. Very helpful in my class.
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