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  • (6)Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Third Edition, Prentice Hall, 2008.

    THE leader in the field for more than twenty years, this introduction to basic concepts and methodologies for digital image processing continues its cutting-edge focus on contemporary developments in all mainstream areas of image processing. Completely self-contained, heavily illustrated, and mathematically accessible, it has a scope of application that is not limited to the solution of specialized problems. Digital Image Fundamentals. Image Enhancement in the Spatial Domain. Image Enhancement in the Frequency Domain. Image Restoration. Color Image Processing. Wavelets and Multiresolution Processing. Image Compression. Morphological Image Processing. Image Segmentation. Representation and Description. Object Recognition. For technicians interested in the fundamentals and contemporary applications of digital imaging processing

  • (7)William K. Pratt, Digital Image Processing, Third Edition, Wiley, 2001.
  • It's a classic. Pratt put a lot of work and detail into it, and it does contains the basics. It also has typo's on some (bunches) of the formula's, transforms, etc. that are annoying if you know about them (hazardous if you don't). Due to the bugs, this would not be my first choice in a DIP book, but I don't know which one would, either. If you are forced into it, find an errata for this book and mark it up, then the book will serve you well.

  • (8)Rafael C. Gonzalez, Richard E. Woods, Steven L Eddins, Digital Image Processing using MATLAB, Prentice Hall, 2004

    If you want to get up to speed on Matlab and plan to use it for image processing, this book is a must.
    I have lots of experience in computer graphics and in programming languages like C++ and C#, but prior to reading this book I had never really used Matlab nor implemented complicated image processing algorithms. This book is a great introduction to both. The book is divided in twelve chapters touching both low-level image processing (e.g. spatial filtering) and higher-level concepts required for computer vision, like image registration and segmentation. The only potential downside of this book is that it's definitely designed to be read sequentially, one chapter at a time. and a reader with less time to cover all of the matter may find this to be a problem.

  • (9)Milan Sonka, Vaclav Hlavac, Roger Boyle, Image Processing, Analysis and Machine Vision, Second Edition, PWS, 1999
    I found this book too mathematical and very sparse when actually trying to help myself on an image processing course. It covers quite a lot of ground, but there's almost more math than english. You get the feeling the authors are very comfortable with this, and to be honest if you have done a maths-based degree it'll be fine for you. But then again, you may find it treats topics lightly and constantly refers to other papers, as if you live in a good science library or something.

  • (10)Anil K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989
    This book probably has all the information you need to know about digital image processing. However, if you are new to the field, this book may be your worst nightmare: It is really difficult to read and understand. So, if you want to learn about digital image processing, buy an easy to read book -such as the one from Gonzales- and get this book as a reference book.

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