Image Processing And Analysis With Graphs
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Image Processing And Analysis With Graphs
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Author : Olivier Lezoray
language : en
Publisher: CRC Press
Release Date : 2017-07-12
Image Processing And Analysis With Graphs written by Olivier Lezoray and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Computers categories.
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.
Graph Spectral Image Processing
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Author : Gene Cheung
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-31
Graph Spectral Image Processing written by Gene Cheung and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Computers categories.
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.
Graphs In Biomedical Image Analysis And Integrating Medical Imaging And Non Imaging Modalities
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Author : Danail Stoyanov
language : en
Publisher: Springer
Release Date : 2018-09-15
Graphs In Biomedical Image Analysis And Integrating Medical Imaging And Non Imaging Modalities written by Danail Stoyanov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-15 with Computers categories.
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
Graph Based Methods In Computer Vision Developments And Applications
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Author : Bai, Xiao
language : en
Publisher: IGI Global
Release Date : 2012-07-31
Graph Based Methods In Computer Vision Developments And Applications written by Bai, Xiao and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-31 with Computers categories.
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.
Uncertainty For Safe Utilization Of Machine Learning In Medical Imaging And Graphs In Biomedical Image Analysis
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Author : Carole H. Sudre
language : en
Publisher: Springer Nature
Release Date : 2020-10-05
Uncertainty For Safe Utilization Of Machine Learning In Medical Imaging And Graphs In Biomedical Image Analysis written by Carole H. Sudre and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-05 with Computers categories.
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.
Graph Based Representations In Pattern Recognition
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Author : Jean-Michel Jolion
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Graph Based Representations In Pattern Recognition written by Jean-Michel Jolion and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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.
Digital Image Analysis
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Author : Walter Kropatsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-10
Digital Image Analysis written by Walter Kropatsch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-10 with Computers categories.
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.
Graph Based Representations In Pattern Recognition
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Author : Luc Brun
language : en
Publisher: Springer
Release Date : 2005-03-10
Graph Based Representations In Pattern Recognition written by Luc Brun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-03-10 with Computers categories.
Many vision problems have to deal with di?erent entities (regions, lines, line junctions, etc.) and their relationships. These entities together with their re- tionships may be encoded using graphs or hypergraphs. The structural inf- mation encoded by graphs allows computer vision algorithms to address both the features of the di?erent entities and the structural or topological relati- ships between them. Moreover, turning a computer vision problem into a graph problem allows one to access the full arsenal of graph algorithms developed in computer science. The Technical Committee (TC15, http://www.iapr.org/tcs.html) of the IAPR (International Association for Pattern Recognition) has been funded in order to federate and to encourage research work in these ?elds. Among its - tivities, TC15 encourages the organization of special graph sessions at many computer vision conferences and organizes the biennial workshop GbR. While being designed within a speci?c framework, the graph algorithms developed for computer vision and pattern recognition tasks often share constraints and goals with those developed in other research ?elds such as data mining, robotics and discrete geometry. The TC15 community is thus not closed in its research ?elds but on the contrary is open to interchanges with other groups/communities.
Graphs In Biomedical Image Analysis Computational Anatomy And Imaging Genetics
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Author : M. Jorge Cardoso
language : en
Publisher: Springer
Release Date : 2017-09-06
Graphs In Biomedical Image Analysis Computational Anatomy And Imaging Genetics written by M. Jorge Cardoso and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-06 with Computers categories.
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.
Design Of Image Processing Embedded Systems Using Multidimensional Data Flow
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Author : Joachim Keinert
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-18
Design Of Image Processing Embedded Systems Using Multidimensional Data Flow written by Joachim Keinert and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-18 with Technology & Engineering categories.
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.