Mathematical Methods For Signal And Image Analysis And Representation
Download Mathematical Methods For Signal And Image Analysis And Representation full books in PDF, epub, and Kindle. Read online free Mathematical Methods For Signal And Image Analysis And Representation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads.
Author |
: Luc Florack |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 321 |
Release |
: 2012-01-12 |
ISBN-10 |
: 9781447123538 |
ISBN-13 |
: 1447123530 |
Rating |
: 4/5 (38 Downloads) |
Synopsis Mathematical Methods for Signal and Image Analysis and Representation by : Luc Florack
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.
Author |
: Luc Florack |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 321 |
Release |
: 2012-01-13 |
ISBN-10 |
: 9781447123521 |
ISBN-13 |
: 1447123522 |
Rating |
: 4/5 (21 Downloads) |
Synopsis Mathematical Methods for Signal and Image Analysis and Representation by : Luc Florack
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.
Author |
: Charles L. Byrne |
Publisher |
: CRC Press |
Total Pages |
: 441 |
Release |
: 2014-11-12 |
ISBN-10 |
: 9781482241846 |
ISBN-13 |
: 1482241846 |
Rating |
: 4/5 (46 Downloads) |
Synopsis Signal Processing by : Charles L. Byrne
Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics—including familiarity with Fourier series, matrices, probability, and statistics—this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters Expands the material on Fourier analysis to three new chapters to provide additional background information Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.
Author |
: Yehoshua Zeevi |
Publisher |
: Academic Press |
Total Pages |
: 603 |
Release |
: 1998-02-09 |
ISBN-10 |
: 9780080541174 |
ISBN-13 |
: 0080541178 |
Rating |
: 4/5 (74 Downloads) |
Synopsis Signal and Image Representation in Combined Spaces by : Yehoshua Zeevi
This volume explains how the recent advances in wavelet analysis provide new means for multiresolution analysis and describes its wide array of powerful tools. The book covers variations of the windowed Fourier transform, constructions of special waveforms suitable for specific tasks, the use of redundant representations in reconstruction and enhancement, applications of efficient numerical compression as a tool for fast numerical analysis, and approximation properties of various waveforms in different contexts.
Author |
: Tony F. Chan |
Publisher |
: SIAM |
Total Pages |
: 414 |
Release |
: 2005-09-01 |
ISBN-10 |
: 9780898715897 |
ISBN-13 |
: 089871589X |
Rating |
: 4/5 (97 Downloads) |
Synopsis Image Processing and Analysis by : Tony F. Chan
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.
Author |
: Todd K. Moon |
Publisher |
: Pearson |
Total Pages |
: 990 |
Release |
: 2000 |
ISBN-10 |
: STANFORD:36105024186244 |
ISBN-13 |
: |
Rating |
: 4/5 (44 Downloads) |
Synopsis Mathematical Methods and Algorithms for Signal Processing by : Todd K. Moon
This previously included a CD. The CD contents can be accessed via World Wide Web.
Author |
: A.A. Petrosian |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 548 |
Release |
: 2013-03-09 |
ISBN-10 |
: 9789401597159 |
ISBN-13 |
: 9401597154 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Wavelets in Signal and Image Analysis by : A.A. Petrosian
Despite their novelty, wavelets have a tremendous impact on a number of modern scientific disciplines, particularly on signal and image analysis. Because of their powerful underlying mathematical theory, they offer exciting opportunities for the design of new multi-resolution processing algorithms and effective pattern recognition systems. This book provides a much-needed overview of current trends in the practical application of wavelet theory. It combines cutting edge research in the rapidly developing wavelet theory with ideas from practical signal and image analysis fields. Subjects dealt with include balanced discussions on wavelet theory and its specific application in diverse fields, ranging from data compression to seismic equipment. In addition, the book offers insights into recent advances in emerging topics such as double density DWT, multiscale Bayesian estimation, symmetry and locality in image representation, and image fusion. Audience: This volume will be of interest to graduate students and researchers whose work involves acoustics, speech, signal and image processing, approximations and expansions, Fourier analysis, and medical imaging.
Author |
: Michael Elad |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 376 |
Release |
: 2010-08-12 |
ISBN-10 |
: 9781441970114 |
ISBN-13 |
: 1441970118 |
Rating |
: 4/5 (14 Downloads) |
Synopsis Sparse and Redundant Representations by : Michael Elad
A long long time ago, echoing philosophical and aesthetic principles that existed since antiquity, William of Ockham enounced the principle of parsimony, better known today as Ockham’s razor: “Entities should not be multiplied without neces sity. ” This principle enabled scientists to select the ”best” physical laws and theories to explain the workings of the Universe and continued to guide scienti?c research, leadingtobeautifulresultsliketheminimaldescriptionlength approachtostatistical inference and the related Kolmogorov complexity approach to pattern recognition. However, notions of complexity and description length are subjective concepts anddependonthelanguage“spoken”whenpresentingideasandresults. The?eldof sparse representations, that recently underwent a Big Bang like expansion, explic itly deals with the Yin Yang interplay between the parsimony of descriptions and the “language” or “dictionary” used in them, and it became an extremely exciting area of investigation. It already yielded a rich crop of mathematically pleasing, deep and beautiful results that quickly translated into a wealth of practical engineering applications. You are holding in your hands the ?rst guide book to Sparseland, and I am sure you’ll ?nd in it both familiar and new landscapes to see and admire, as well as ex cellent pointers that will help you ?nd further valuable treasures. Enjoy the journey to Sparseland! Haifa, Israel, December 2009 Alfred M. Bruckstein vii Preface This book was originally written to serve as the material for an advanced one semester (fourteen 2 hour lectures) graduate course for engineering students at the Technion, Israel.
Author |
: Tony F. Chan |
Publisher |
: SIAM |
Total Pages |
: 421 |
Release |
: 2005-01-01 |
ISBN-10 |
: 0898717876 |
ISBN-13 |
: 9780898717877 |
Rating |
: 4/5 (76 Downloads) |
Synopsis Image Processing and Analysis by : Tony F. Chan
At no other time in human history have the influence and impact of image processing on modern society, science, and technology been so explosive. Image processing has become a critical component in contemporary science and technology and has many important applications. This book develops the mathematical foundation of modern image processing and low-level computer vision, and presents a general framework from the analysis of image structures and patterns to their processing. The core mathematical and computational ingredients of several important image processing tasks are investigated. The book bridges contemporary mathematics with state-of-the-art methodologies in modern image processing while organizing the vast contemporary literature into a coherent and logical structure.
Author |
: Gabriele Moser |
Publisher |
: Springer |
Total Pages |
: 446 |
Release |
: 2017-11-28 |
ISBN-10 |
: 9783319663302 |
ISBN-13 |
: 3319663305 |
Rating |
: 4/5 (02 Downloads) |
Synopsis Mathematical Models for Remote Sensing Image Processing by : Gabriele Moser
This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses highly topical subjects involving remote sensing data types (e.g., very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g., probabilistic graphical models, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.