Stochastic Geometry For Image Analysis
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Stochastic Geometry For Image Analysis
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Author : Xavier Descombes
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-06
Stochastic Geometry For Image Analysis written by Xavier Descombes 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 2013-05-06 with Technology & Engineering categories.
This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
Stochastic Geometry
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Author : David Coupier
language : en
Publisher: Springer
Release Date : 2019-04-09
Stochastic Geometry written by David Coupier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-09 with Mathematics categories.
This volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures. The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject: understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes. Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications.
From Gestalt Theory To Image Analysis
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Author : Agnès Desolneux
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-24
From Gestalt Theory To Image Analysis written by Agnès Desolneux 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 2007-12-24 with Computers categories.
This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The book is mathematically self-contained, needing only basic understanding of probability and calculus. The text includes more than 130 illustrations, and numerous examples based on specific images on which the theory is tested. Detailed exercises at the end of each chapter help the reader develop a firm understanding of the concepts imparted.
Image Processing And Analysis
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Author : Tony F. Chan
language : en
Publisher: SIAM
Release Date : 2005-09-01
Image Processing And Analysis written by Tony F. Chan and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-01 with Computers categories.
This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.
Mathematical Nonlinear Image Processing
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Author : Edward R. Dougherty
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Mathematical Nonlinear Image Processing written by Edward R. Dougherty 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.
Mathematical Nonlinear Image Processing deals with a fast growing research area. The development of the subject springs from two factors: (1) the great expansion of nonlinear methods applied to problems in imaging and vision, and (2) the degree to which nonlinear approaches are both using and fostering new developments in diverse areas of mathematics. Mathematical Nonlinear Image Processing will be of interest to people working in the areas of applied mathematics as well as researchers in computer vision. Mathematical Nonlinear Image Processing is an edited volume of original research. It has also been published as a special issue of the Journal of Mathematical Imaging and Vision. (Volume 2, Issue 2/3).
Stochastic Geometry Models In Image Analysis And Spatial Statistics
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Author : M. N. M. Van Lieshout
language : en
Publisher:
Release Date : 1991
Stochastic Geometry Models In Image Analysis And Spatial Statistics written by M. N. M. Van Lieshout and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with categories.
Image Analysis
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Author : Josef Bigun
language : en
Publisher: Springer
Release Date : 2003-08-02
Image Analysis written by Josef Bigun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-02 with Computers categories.
This book constitutes the refeered proceedings of the 13th Scandinavian Conference on Image Analysis, SCIA 2003, held in Halmstad, Sweden in June/July 2003. The 148 revised full papers presented together with 6 invited contributions were carefully reviewed and selected for presentation. The papers are organized in topical sections on feature extraction, depth and surface, shape analysis, coding and representation, motion analysis, medical image processing, color analysis, texture analysis, indexing and categorization, and segmentation and spatial grouping.
Perfect And Imperfect Simulations In Stochastic Geometry In Image Analysis
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Author : Elke Thönnes
language : en
Publisher:
Release Date : 1998
Perfect And Imperfect Simulations In Stochastic Geometry In Image Analysis written by Elke Thönnes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Stochastic Geometry
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Author : Wilfrid S. Kendall
language : en
Publisher: CRC Press
Release Date : 1998-10-20
Stochastic Geometry written by Wilfrid S. Kendall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-20 with Mathematics categories.
Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including: o a "crash-course" introduction to key stochastic geometry themes o considerations of geometric sampling bias issues o tesselations o shape o random sets o image analysis o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo
Mathematical Foundations Of Image Processing And Analysis Volume 2
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Author : Jean-Charles Pinoli
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-22
Mathematical Foundations Of Image Processing And Analysis Volume 2 written by Jean-Charles Pinoli 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 2014-07-22 with Technology & Engineering categories.
Mathematical Imaging is currently a rapidly growing field in applied mathematics, with an increasing need for theoretical mathematics. This book, the second of two volumes, emphasizes the role of mathematics as a rigorous basis for imaging sciences. It provides a comprehensive and convenient overview of the key mathematical concepts, notions, tools and frameworks involved in the various fields of gray-tone and binary image processing and analysis, by proposing a large, but coherent, set of symbols and notations, a complete list of subjects and a detailed bibliography. It establishes a bridge between the pure and applied mathematical disciplines, and the processing and analysis of gray-tone and binary images. It is accessible to readers who have neither extensive mathematical training, nor peer knowledge in Image Processing and Analysis. It is a self-contained book focusing on the mathematical notions, concepts, operations, structures, and frameworks that are beyond or involved in Image Processing and Analysis. The notations are simplified as far as possible in order to be more explicative and consistent throughout the book and the mathematical aspects are systematically discussed in the image processing and analysis context, through practical examples or concrete illustrations. Conversely, the discussed applicative issues allow the role of mathematics to be highlighted. Written for a broad audience – students, mathematicians, image processing and analysis specialists, as well as other scientists and practitioners – the author hopes that readers will find their own way of using the book, thus providing a mathematical companion that can help mathematicians become more familiar with image processing and analysis, and likewise, image processing and image analysis scientists, researchers and engineers gain a deeper understanding of mathematical notions and concepts.