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A volume in the
Digital Imaging and Computer Vision series
Image Processing and Analysis with
Graphs: Theory and Practice
Edited by:
Olivier Lézoray* and Leo Grady**
*University of Caen, France
**Siemens Corporate Research, Princeton, New Jersey, USA
Boca Raton, FL, CRC Press / Taylor & Francis, July 2012
ISBN 978-1-4398-5507-2
Audience:
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Academic community (graduate student, post-doc and
faculty) in Electrical Engineering, Computer Science, and Applied
Mathematics |
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Industrial community (engineers,
engineering managers, and research lab staff) |
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Covering the theoretical aspects of
image processing and analysis through the use of graphs in the
representation and analysis of objects, Image Processing and Analysis
with Graphs: Theory and Practice also demonstrates how these
concepts are indispensable for the design of cutting-edge solutions for
real-world applications. With
the explosive growth in image production, in everything from digital
photographs to medical scans, there has been a drastic increase in the
number of applications based on digital images. This book explores how
graphs - which are suitable to represent any discrete data by modeling
neighborhood relationships have emerged as the perfect unified tool to
represent, process, and analyze images. It also explain why graphs are
ideal for defining graph-theoretical algorithms that enable the
processing of functions, making it possible to draw on the rich
literature of combinatorial optimization to produce highly efficient
solutions.
Some key subjects in the book include:
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Definition of graph-theoretical
algorithms that enable denoising and image enhancement |
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Energy minimization and modeling of
pixel-labeling problems with graph cuts and Markov random fields |
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Image processing with graphs:
targeted segmentation, partial differential equations, mathematical
morphology, and wavelets |
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Analysis of the similarity between
objects with graph matching |
Use of graphs become very influential
in computer science and has led to many applications in denoising,
enhancement, restoration, and object extraction. Accounting for the wide
variety of imaging problems being solved with graphs, this contributed
volume presents a number of state-of-the-art methods and application
examples.
Features:
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Provides a comprehensive overview
of graphs in image processing, image analysis, computer vision, and
pattern recognition |
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Explains the latest techniques,
algorithms, and solutions for processing and analyzing images with
graphs |
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Explores new applications in
computational photography, computer vision, image and video
processing, computer graphics, and medical and biomedical imaging |
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Contains examples, illustrations,
and tables summarizing results from quantitative studies |
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