Geometric Methods in Signal and Image Analysis

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Publisher : Cambridge University Press
ISBN 13 : 1316351963
Total Pages : 299 pages
Book Rating : 4.63/5 ( download)

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Book Synopsis Geometric Methods in Signal and Image Analysis by : Hamid Krim

Download or read book Geometric Methods in Signal and Image Analysis written by Hamid Krim and published by Cambridge University Press. This book was released on 2015-06-18 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive guide offers a new approach for developing and implementing robust computational methodologies that uncover the key geometric and topological information from signals and images. With the help of detailed real-world examples and applications, readers will learn how to solve complex signal and image processing problems in fields ranging from remote sensing to medical imaging, bioinformatics, robotics, security, and defence. With an emphasis on intuitive and application-driven arguments, this text covers not only a range of methods in use today, but also introduces promising new developments for the future, bringing the reader up-to-date with the state of the art in signal and image analysis. Covering basic principles as well as advanced concepts and applications, and with examples and homework exercises, this is an invaluable resource for graduate students, researchers, and industry practitioners in a range of fields including signal and image processing, biomedical engineering, and computer graphics.

Riemannian Geometric Statistics in Medical Image Analysis

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Publisher : Academic Press
ISBN 13 : 0128147261
Total Pages : 636 pages
Book Rating : 4.69/5 ( download)

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Book Synopsis Riemannian Geometric Statistics in Medical Image Analysis by : Xavier Pennec

Download or read book Riemannian Geometric Statistics in Medical Image Analysis written by Xavier Pennec and published by Academic Press. This book was released on 2019-09-02 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology Content includes: The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs Applications of statistics on manifolds and shape spaces in medical image computing Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. A complete reference covering both the foundations and state-of-the-art methods Edited and authored by leading researchers in the field Contains theory, examples, applications, and algorithms Gives an overview of current research challenges and future applications

Computational Information Geometry

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Publisher : Springer
ISBN 13 : 3319470582
Total Pages : 299 pages
Book Rating : 4.80/5 ( download)

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Book Synopsis Computational Information Geometry by : Frank Nielsen

Download or read book Computational Information Geometry written by Frank Nielsen and published by Springer. This book was released on 2016-11-24 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals. It provides introductory chapters to help those new to information geometry and applies the theory to several applications. This area has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition and the desire to process and interpret large databases of digital information. The book addresses both the transfer of methodology to practitioners involved in database analysis and in its efficient computational implementation.

Mathematical Methods for Signal and Image Analysis and Representation

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Publisher : Springer Science & Business Media
ISBN 13 : 1447123522
Total Pages : 321 pages
Book Rating : 4.21/5 ( download)

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Book Synopsis Mathematical Methods for Signal and Image Analysis and Representation by : Luc Florack

Download or read book Mathematical Methods for Signal and Image Analysis and Representation written by Luc Florack and published by Springer Science & Business Media. This book was released on 2012-01-13 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.

Sparse Image and Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 1107088062
Total Pages : 449 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis Sparse Image and Signal Processing by : Jean-Luc Starck

Download or read book Sparse Image and Signal Processing written by Jean-Luc Starck and published by Cambridge University Press. This book was released on 2015-10-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents state-of-the-art sparse and multiscale image and signal processing with applications in astronomy, biology, MRI, media, and forensics.

Geometric Modeling for Scientific Visualization

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Publisher : Springer Science & Business Media
ISBN 13 : 3662074435
Total Pages : 473 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Geometric Modeling for Scientific Visualization by : Guido Brunnett

Download or read book Geometric Modeling for Scientific Visualization written by Guido Brunnett and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geometric Modeling and Scientific Visualization are both established disciplines, each with their own series of workshops, conferences and journals. But clearly both disciplines overlap; this observation led to the idea of composing a book on Geometric Modeling for Scientific Visualization.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Publisher : Springer
ISBN 13 : 3642102689
Total Pages : 1082 pages
Book Rating : 4.84/5 ( download)

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Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : Eduardo Bayro-Corrochano

Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by Eduardo Bayro-Corrochano and published by Springer. This book was released on 2009-11-16 with total page 1082 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 14th Iberoamerican Congress on Pattern Recognition (CIARP 2009, C- gresoIberoAmericanodeReconocimientodePatrones)formedthelatestofanow longseriesofsuccessfulmeetingsarrangedbytherapidlygrowingIberoamerican pattern recognition community. The conference was held in Guadalajara, Jalisco, Mexico and organized by the Mexican Association for Computer Vision, Neural Computing and Robotics (MACVNR). It was sponsodred by MACVNR and ?ve other Iberoamerican PR societies. CIARP 2009 was like the previous conferences in the series supported by the International Association for Pattern Recognition (IAPR). CIARP 2009 attracted participants from all over the world presenting sta- of-the-artresearchon mathematical methods and computing techniques for p- tern recognition, computer vision, image and signal analysis, robot vision, and speech recognition, as well as on a wide range of their applications. This time the conference attracted participants from 23 countries,9 in Ibe- america, and 14 from other parts of the world. The total number of submitted papers was 187, and after a serious review process 108 papers were accepted, all of them with a scienti?c quality above overall mean rating. Sixty-four were selected as oral presentations and 44 as posters. Since 2008 the conference is almost single track, and therefore there was no real grading in quality between oral and poster papers. As an acknowledgment that CIARP has established itself as a high-quality conference, its proceedings appear in the Lecture Notes in Computer Science series. Moreover, its visibility is further enhanced by a selection of a set of papers that will be published in a special issue of the journal Pattern Recognition Letters.

Image Processing and Analysis

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Publisher : SIAM
ISBN 13 : 089871589X
Total Pages : 414 pages
Book Rating : 4.97/5 ( download)

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Book Synopsis Image Processing and Analysis by : Tony F. Chan

Download or read book Image Processing and Analysis written by Tony F. Chan and published by SIAM. This book was released on 2005-09-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Geometric Level Set Methods in Imaging, Vision, and Graphics

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Publisher : Springer Science & Business Media
ISBN 13 : 0387218106
Total Pages : 523 pages
Book Rating : 4.06/5 ( download)

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Book Synopsis Geometric Level Set Methods in Imaging, Vision, and Graphics by : Stanley Osher

Download or read book Geometric Level Set Methods in Imaging, Vision, and Graphics written by Stanley Osher and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilation of survey chapters from the leading researchers in the field. The applications of the methods are emphasized.

Front-End Vision and Multi-Scale Image Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 140208840X
Total Pages : 470 pages
Book Rating : 4.07/5 ( download)

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Book Synopsis Front-End Vision and Multi-Scale Image Analysis by : Bart M. Haar Romeny

Download or read book Front-End Vision and Multi-Scale Image Analysis written by Bart M. Haar Romeny and published by Springer Science & Business Media. This book was released on 2008-10-24 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.