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E-Book Details:

Digital Image Processing
Prentice Hall
Rafael C. Gonzalez, Richard E. Woods
2nd, illustrated 2002
PDF
0201180758
978-0201180756
800
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.
ABOUT THE AUTHOR:
Rafael C. Gonzalezreceived 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.
  • This edition of Digital Image Processing is a major revision and is based on the most extensive survey the authors have ever conducted. The survey involved faculty, students, and independent readers of the book in 134 institutions from 32 countries. The results have prompted the following new and reorganized material:
  • Expanded homework sets, including over 80 new problems.
  • New examples and illustrations involving over 400 new images and more than 200 new drawings and tables.
  • Companion web site has been redesigned and upgraded to correspond to this new edition.
  • A revision of introductory concepts that provides readers with foundation material much earlier in the book than before.
  • A revised and updated discussion of intensity transformation, spatial correlation, convolution, and their application to spatial filtering.
  • New discussion of fuzzy sets and their application to image processing.
  • A new chapter on the discrete Fourier transform and frequency domain processing.
  • New coverage of computerized tomography.
  • Additional examples dealing with wavelets.
  • A new chapter on data compression, including new compression techniques, digital video compression, standards, and watermarking.
  • New coverage of morphological reconstruction, gray-scale morphology, and advanced morphological algorithms.
  • New coverage of the Marr-Hildreth and Canny edge detection algorithms.
  • Expanded coverage of image thresholding.
  • Updated bibliography
Table of Contents:
Introduction : Examples of fields that use digital image processing, fundamental steps in digital image processing,components of image processing system. Digital Image Fundamentals: A simple image formation model, image sampling and quantization, basic relationships between pixels (p.nos. 15-17, 21- 44,50-69).
Image enhancement in the spatial domain : Basic gray-level transformation, histogram processing,
enhancement using arithmetic and logic operators, basic spatial filtering, smoothing and sharpening spatial filters, combining the spatial enhancement methods ( p.nos 76-141).
Image restoration : A model of the image degradation/restoration process, noise models, restoration in the presence of noise–only spatial filtering, Weiner filtering, constrained least squares filtering, geometric transforms; Introduction to the Fourier transform and the frequency domain, estimating the degradation function (p.nos 147-167, 220-243, 256-276).
Color Image Processing : Color fundamentals, color models, pseudo color image processing, basics of full–color image processing, color transforms, smoothing and sharpening, color segmentation (p.nos: 282- 339).
Image Compression : Fundamentals, image compression models, error-free compression, lossypredictiv coding, image compression standards (p.nos: 409-467,492-510).
Morphological Image Processing : Preliminaries, dilation, erosion, open and closing, hit or miss
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transformation, basic morphologic algorithms (p.nos:519-550).

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Image Segmentation : Detection of discontinuous, edge linking and boundary detection, thresholding, region–based segmentation (p.nos: 567-617).

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Object Recognition : Patterns and patterns classes, recognition based on decision–theoretic methods,matching, optimum statistical classifiers, neural networks, structural methods – matching shape numbers, string matching (p.nos: 693-735).