Perceptual Digital Imaging
Computational Photography
Single-Sensor Imaging
Color Image Processing
Super-Resolution Imaging
Cultural Heritage Imaging
Visual Cryptography
Graphs: Theory & Practice
Image Restoration


A new book on Graphs-Driven Image Processing and Analysis published!

Explore new techniques and applications of graphs in digital imaging!

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


Academic community (graduate student, post-doc and faculty) in Electrical Engineering, Computer Science, and Applied Mathematics


Industrial community (engineers, engineering managers, and research lab staff)


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:

Definition of graph-theoretical algorithms that enable denoising and image enhancement


Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov random fields


Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets


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.


Provides a comprehensive overview of graphs in image processing, image analysis, computer vision, and pattern recognition


Explains the latest techniques, algorithms, and solutions for processing and analyzing images with graphs


Explores new applications in computational photography, computer vision, image and video processing, computer graphics, and medical and biomedical imaging


Contains examples, illustrations, and tables summarizing results from quantitative studies

Additional material is available at the companion web site www.colorimageprocessing.org.

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Last update: 08/03/12

© 2006 Rastislav Lukac