Image Processing And Analysis With Graphs

Author : Olivier Lezoray,Leo Grady
Publisher : CRC Press
Page : 570 pages
File Size : 48,9 Mb
Release : 2017-07-12
Category : Computers
ISBN : 9781439855089

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Image Processing and Analysis with Graphs by Olivier Lezoray,Leo Grady Pdf

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.

Author : Gene Cheung,Enrico Magli
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 54,5 Mb
Release : 2021-08-31
Category : Computers
ISBN : 9781789450286

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Graph Spectral Image Processing by Gene Cheung,Enrico Magli Pdf

Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.

Author : Danail Stoyanov,Zeike Taylor,Enzo Ferrante,Adrian V. Dalca,Anne Martel,Lena Maier-Hein,Sarah Parisot,Aristeidis Sotiras,Bartlomiej Papiez,Mert R. Sabuncu,Li Shen
Publisher : Springer
Page : 101 pages
File Size : 41,6 Mb
Release : 2018-09-15
Category : Computers
ISBN : 9783030006891

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Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities by Danail Stoyanov,Zeike Taylor,Enzo Ferrante,Adrian V. Dalca,Anne Martel,Lena Maier-Hein,Sarah Parisot,Aristeidis Sotiras,Bartlomiej Papiez,Mert R. Sabuncu,Li Shen Pdf

This book constitutes the refereed joint proceedings of the Second International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2018 and the First International Workshop on Integrating Medical Imaging and Non-Imaging Modalities, Beyond MIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 6 full papers presented at GRAIL 2018 and the 5 full papers presented at BeYond MIC 2018 were carefully reviewed and selected. The GRAIL papers cover a wide range of develop graph-based models for the analysis of biomedical images and encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. The Beyond MIC papers cover topics of novel methods with significant imaging and non-imaging components, addressing practical applications and new datasets

Author : Bai, Xiao
Publisher : IGI Global
Page : 395 pages
File Size : 50,6 Mb
Release : 2012-07-31
Category : Computers
ISBN : 9781466618923

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Graph-Based Methods in Computer Vision: Developments and Applications by Bai, Xiao Pdf

Computer vision, the science and technology of machines that see, has been a rapidly developing research area since the mid-1970s. It focuses on the understanding of digital input images in many forms, including video and 3-D range data. Graph-Based Methods in Computer Vision: Developments and Applications presents a sampling of the research issues related to applying graph-based methods in computer vision. These methods have been under-utilized in the past, but use must now be increased because of their ability to naturally and effectively represent image models and data. This publication explores current activity and future applications of this fascinating and ground-breaking topic.

Author : Carole H. Sudre,Hamid Fehri,Tal Arbel,Christian F. Baumgartner,Adrian Dalca,Ryutaro Tanno,Koen Van Leemput,William M. Wells,Aristeidis Sotiras,Bartlomiej Papiez,Enzo Ferrante,Sarah Parisot
Publisher : Springer Nature
Page : 233 pages
File Size : 52,9 Mb
Release : 2020-10-05
Category : Computers
ISBN : 9783030603656

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis by Carole H. Sudre,Hamid Fehri,Tal Arbel,Christian F. Baumgartner,Adrian Dalca,Ryutaro Tanno,Koen Van Leemput,William M. Wells,Aristeidis Sotiras,Bartlomiej Papiez,Enzo Ferrante,Sarah Parisot Pdf

This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

Author : M. Jorge Cardoso,Tal Arbel,Enzo Ferrante,Xavier Pennec,Adrian V. Dalca,Sarah Parisot,Sarang Joshi,Nematollah K. Batmanghelich,Aristeidis Sotiras,Mads Nielsen,Mert R. Sabuncu,Tom Fletcher,Li Shen,Stanley Durrleman,Stefan Sommer
Publisher : Springer
Page : 262 pages
File Size : 49,6 Mb
Release : 2017-09-06
Category : Computers
ISBN : 9783319676753

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Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics by M. Jorge Cardoso,Tal Arbel,Enzo Ferrante,Xavier Pennec,Adrian V. Dalca,Sarah Parisot,Sarang Joshi,Nematollah K. Batmanghelich,Aristeidis Sotiras,Mads Nielsen,Mert R. Sabuncu,Tom Fletcher,Li Shen,Stanley Durrleman,Stefan Sommer Pdf

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.

Author : Gene Cheung,Enrico Magli
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 52,7 Mb
Release : 2021-08-16
Category : Computers
ISBN : 9781119850816

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Graph Spectral Image Processing by Gene Cheung,Enrico Magli Pdf

Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.

Author : Jean-Michel Jolion,Walter Kropatsch
Publisher : Springer Science & Business Media
Page : 149 pages
File Size : 48,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783709164877

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Graph Based Representations in Pattern Recognition by Jean-Michel Jolion,Walter Kropatsch Pdf

Graph-based representation of images is becoming a popular tool since it represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between parts. Therefore, it is widely used to control the different levels from segmentation to interpretation. The 14 papers in this volume are grouped in the following subject areas: hypergraphs, recognition and detection, matching, segmentation, implementation problems, representation.

Author : Walter Kropatsch,Horst Bischof
Publisher : Springer Science & Business Media
Page : 513 pages
File Size : 42,7 Mb
Release : 2006-05-10
Category : Computers
ISBN : 9780387216430

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Digital Image Analysis by Walter Kropatsch,Horst Bischof Pdf

The challenge behind the processing of digital images is the huge amounts of data that has to be processed in an extremely short period of time. This book is a broad-ranging technical survey of computational and analytical methods and tools for digital image analysis and interpretation. The ultimate goal is to create a rich set of computational methods for image analysis and interpretation that can achieve rapid response times. This book will serve as an excellent up-to-date resource for computer scientists and engineers in digital imaging and analysis.

Author : Jean Claude Simon,Azriel Rosenfeld
Publisher : Noordhoff International Publishing
Page : 532 pages
File Size : 46,9 Mb
Release : 1977
Category : Computers
ISBN : UCAL:B4532108

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Digital Image Processing and Analysis by Jean Claude Simon,Azriel Rosenfeld Pdf

Author : Antonio Ortega
Publisher : Cambridge University Press
Page : 128 pages
File Size : 50,9 Mb
Release : 2022-06-09
Category : Technology & Engineering
ISBN : 9781108640176

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Introduction to Graph Signal Processing by Antonio Ortega Pdf

An intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.

Author : Ljubiša Stanković,Ervin Sejdić
Publisher : Springer
Page : 507 pages
File Size : 43,5 Mb
Release : 2018-12-01
Category : Technology & Engineering
ISBN : 9783030035747

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Vertex-Frequency Analysis of Graph Signals by Ljubiša Stanković,Ervin Sejdić Pdf

This book introduces new methods to analyze vertex-varying graph signals. In many real-world scenarios, the data sensing domain is not a regular grid, but a more complex network that consists of sensing points (vertices) and edges (relating the sensing points). Furthermore, sensing geometry or signal properties define the relation among sensed signal points. Even for the data sensed in the well-defined time or space domain, the introduction of new relationships among the sensing points may produce new insights in the analysis and result in more advanced data processing techniques. The data domain, in these cases and discussed in this book, is defined by a graph. Graphs exploit the fundamental relations among the data points. Processing of signals whose sensing domains are defined by graphs resulted in graph data processing as an emerging field in signal processing. Although signal processing techniques for the analysis of time-varying signals are well established, the corresponding graph signal processing equivalent approaches are still in their infancy. This book presents novel approaches to analyze vertex-varying graph signals. The vertex-frequency analysis methods use the Laplacian or adjacency matrix to establish connections between vertex and spectral (frequency) domain in order to analyze local signal behavior where edge connections are used for graph signal localization. The book applies combined concepts from time-frequency and wavelet analyses of classical signal processing to the analysis of graph signals. Covering analytical tools for vertex-varying applications, this book is of interest to researchers and practitioners in engineering, science, neuroscience, genome processing, just to name a few. It is also a valuable resource for postgraduate students and researchers looking to expand their knowledge of the vertex-frequency analysis theory and its applications. The book consists of 15 chapters contributed by 41 leading researches in the field.

Author : Gonzalez, Fabio A.,Romero, Eduardo
Publisher : IGI Global
Page : 390 pages
File Size : 51,5 Mb
Release : 2009-12-31
Category : Computers
ISBN : 9781605669571

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Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques by Gonzalez, Fabio A.,Romero, Eduardo Pdf

Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1587 pages
File Size : 43,6 Mb
Release : 2013-05-31
Category : Computers
ISBN : 9781466639959

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Image Processing: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf

Advancements in digital technology continue to expand the image science field through the tools and techniques utilized to process two-dimensional images and videos. Image Processing: Concepts, Methodologies, Tools, and Applications presents a collection of research on this multidisciplinary field and the operation of multi-dimensional signals with systems that range from simple digital circuits to computers. This reference source is essential for researchers, academics, and students in the computer science, computer vision, and electrical engineering fields.

Author : Joachim Keinert,Jürgen Teich
Publisher : Springer Science & Business Media
Page : 324 pages
File Size : 48,9 Mb
Release : 2010-11-18
Category : Technology & Engineering
ISBN : 9781441971821

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Design of Image Processing Embedded Systems Using Multidimensional Data Flow by Joachim Keinert,Jürgen Teich Pdf

This book presents a new set of embedded system design techniques called multidimensional data flow, which combine the various benefits offered by existing methodologies such as block-based system design, high-level simulation, system analysis and polyhedral optimization. It describes a novel architecture for efficient and flexible high-speed communication in hardware that can be used both in manual and automatic system design and that offers various design alternatives, balancing achievable throughput with required hardware size. This book demonstrates multidimensional data flow by showing its potential for modeling, analysis, and synthesis of complex image processing applications. These applications are presented in terms of their fundamental properties and resulting design constraints. Coverage includes a discussion of how far the latter can be met better by multidimensional data flow than alternative approaches. Based on these results, the book explains the principles of fine-grained system level analysis and high-speed communication synthesis. Additionally, an extensive review of related techniques is given in order to show their relation to multidimensional data flow.