E-Book Details:
Title:
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Digital Image Processing
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Publisher:
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Prentice Hall
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Author:
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Rafael C. Gonzalez, Richard E. Woods
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Edition:
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2nd, illustrated 2002
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Format:
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PDF
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ISBN:
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0201180758
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EAN:
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978-0201180756
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No.ofPages:
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800
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Book 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.
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.
New to this Edition:
- 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.
Table of Contents:
1. Introduction.
What
Is Digital Image Processing? The Origins of Digital Image Processing.
Examples of Fields that Use Digital Image Processing. Fundamental Steps
in Digital Image Processing. Components of an Image Processing System.
2. Digital Image Fundamentals.
2. Digital Image Fundamentals.
Elements
of Visual Perception. Light and the Electromagnetic Spectrum. Image
Sensing and Acquisition. Image Sampling and Quantization. Some Basic
Relationships Between Pixels. Linear and Nonlinear Operations.
3. Image Enhancement in the Spatial Domain.
Background.
Some Basic Gray Level Transformations. Histogram Processing.
Enhancement Using Arithmetic/Logic Operations. Basics of Spatial
Filtering. Smoothing Spatial Filters. Sharpening Spatial Filters.
Combining Spatial Enhancement Methods.
4. Image Enhancement in the Frequency Domain.
Background.
Introduction to the Fourier Transform and the Frequency Domain.
Smoothing Frequency-Domain Filters. Sharpening Frequency Domain Filters.
Homomorphic Filtering. Implementation.
5. Image Restoration.
A
Model of the Image Degradation/Restoration Process. Noise Models.
Restoration in the Presence of Noise Only-Spatial Filtering. Periodic
Noise Reduction by Frequency Domain Filtering. Linear,
Position-Invariant Degradations. Estimating the Degradation Function.
Inverse Filtering. Minimum Mean Square Error (Wiener) Filtering.
Constrained Least Squares Filtering. Geometric Mean Filter. Geometric
Transformations.
6. Color Image Processing.
Color
Fundamentals. Color Models. Pseudocolor Image Processing. Basics of
Full-Color Image Processing. Color Transformations. Smoothing and
Sharpening. Color Segmentation. Noise in Color Images. Color Image
Compression.
7. Wavelets and Multiresolution Processing.
Background.
Multiresolution Expansions. Wavelet Transforms in One Dimension. The
Fast Wavelet Transform. Wavelet Transforms in Two Dimensions. Wavelet
Packets.
8. Image Compression.
Fundamentals.
Image Compression Models. Elements of Information Theory. Error-Free
Compression. Lossy Compression. Image Compression Standards.
9. Morphological Image Processing.
Preliminaries.
Dilation and Erosion. Opening and Closing. The Hit-or-Miss
Transformation. Some Basic Morphological Algorithms. Extensions to
Gray-Scale Images.
10. Image Segmentation.
Detection
of Discontinuities. Edge Linking and Boundary Detection. Thresholding.
Region-Based Segmentation. Segmentation by Morphological Watersheds. The
Use of Motion in Segmentation.
11. Representation and Description.
Representation. Boundary Descriptors. Regional Descriptors. Use of Principal Components for Description. Relational Descriptors.
12. Object Recognition.
Patterns and Pattern Classes. Recognition Based on Decision-Theoretic Methods. Structural Methods.
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