Olivier Lezoray – författare

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 indispensible for the design of cutting-edge solutions for real-world applications.Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imagingWith 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 explains 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 covered 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 Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imagingUse of graphs has 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 problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

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 indispensible for the design of cutting-edge solutions for real-world applications.

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

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 explains 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 covered 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

Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging

Use of graphs has 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 problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

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 indispensible for the design of cutting-edge solutions for real-world applications.Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imagingWith 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 explains 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 covered 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 Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imagingUse of graphs has 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 problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

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 indispensible for the design of cutting-edge solutions for real-world applications.

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

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 explains 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 covered 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

Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging

Use of graphs has 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 problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

The contributions are organized in topical sections on multispectral colour science, color imaging and applications, digital cultural heritage, document image analysis, graph-based representations, image filtering and representation, computer vision and pattern recognition, computer graphics, biomedical, and signal processing.

This book constitutes the refereed proceedings of the 6th International Conference, ICISP 2014, held in June/July 2014 in Cherbourg, France. The 76 revised full papers were carefully reviewed and selected from 164 submissions. The contributions are organized in topical sections on multispectral colour science, color imaging and applications, digital cultural heritage, document image analysis, graph-based representations, image filtering and representation, computer vision and pattern recognition, computer graphics, biomedical, and signal processing.

This book constitutes the refereed proceedings of the Third International Conference on Image and Signal Processing, ICISP 2008, held in Cherbourg-Octeville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, graph-based representations, motion detection and estimation, new interfaces, document processing, and signal processing.

This book constitutes the refereed proceedings of the Third International Conference on Image and Signal Processing, ICISP 2008, held in Cherbourg-Octeville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, graph-based representations, motion detection and estimation, new interfaces, document processing, and signal processing.

ICISP 2010, the International Conference on Image and Signal Processing, was the fourth ICISP conference, and was held in Trois-Rivi' eres, Qu' ebec, Canada. Historically, ICISP is a conference resulting from the actions of researchers of Canada,FranceandMorocco.PreviouseditionsofICISPwereheldinCherbourg- Octeville (France), Agadir (Morocco), and Agadir (Morocco) in 2008, 2003 and 2001, respectively. ICISP 2010 was sponsored by EURASIP (European Assoc- tion for Image and Signal Processing) and IAPR (International Association for Pattern Recognition). The response to the call for papers for ICISP 2010 was encouraging. From 165 full papers submitted, 69 were ?nally accepted (54 oral presentations, and 15 posters). The review process was carried out by the Program Committee members; all are experts in various image and signal processing areas. Each paper was reviewed by atleast two reviewers,and also checkedby the conference Co-chairs. The quality of the papers in these proceedings is attributed ?rst to the authors, and second to the quality of the reviews provided by the experts.We would like to thank the authors for responding to our call, and we thank the reviewers for their excellent work. We wereverypleasedto be ableto include inthe conferenceprogramkeynote talks by three world-renowned experts: Yann Lecun, Silver Professor of C- puter Science and Neural Science, The Courant Institute of Mathematical S- ences and Center for Neural Science, New York University (USA); Theo Gevers, Associate Professor, Faculty of Science, University of Amsterdam (The Neth- lands);andLeoGrady,SeniorMemberofTechnicalSta?withSiemensCorporate Research in Princeton, New Jersey (USA).

This book constitutes the refereed proceedings of the 5th International Conference on Image and Signal Processing, ICISP 2012, held in Agadir, Morocco, in June 2012. The 75 revised full papers presented were carefully reviewed and selected from 158 submissions. The contributions are grouped into the following topical sections: multi/hyperspectral imaging; image itering and coding; signal processing; biometric; watermarking and texture; segmentation and retieval; image processing; pattern recognition.