Mathematical Nonlinear Image Processing
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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).
An Introduction To Nonlinear Image Processing
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Author : Edward R. Dougherty
language : en
Publisher: SPIE Press
Release Date : 1994
An Introduction To Nonlinear Image Processing written by Edward R. Dougherty and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Technology & Engineering categories.
From a strict semantic point of view, nonlinear image processing encompasses all image processing that is not based on linear operators; however, from a practical, evolutionary point of view, the name itself is usually associated with the study of nonlinear filters, mainly the deterministic and nondeterministic analysis and design of logic-based operators. This Tutorial Text volume explores logic-based operators with emphasis on representation, design, and statistical optimization of nonlinear filters.
Nonlinear Image Processing
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Author : Sanjit Mitra
language : en
Publisher: Academic Press
Release Date : 2001
Nonlinear Image Processing written by Sanjit Mitra and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and industrial automation challenges.
Nonlinear Filters For Image Processing
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Author : Edward R. Dougherty
language : en
Publisher: SPIE-International Society for Optical Engineering
Release Date : 1999
Nonlinear Filters For Image Processing written by Edward R. Dougherty and has been published by SPIE-International Society for Optical Engineering this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
This text covers key mathematical principles and algorithms for nonlinear filters used in image processing. Readers will gain an in-depth understanding of the underlying mathematical and filter design methodologies needed to construct and use nonlinear filters in a variety of applications.
Oscillating Patterns In Image Processing And Nonlinear Evolution Equations
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Author : Yves Meyer
language : en
Publisher: American Mathematical Soc.
Release Date : 2001
Oscillating Patterns In Image Processing And Nonlinear Evolution Equations written by Yves Meyer and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
Image compression, the Navier-Stokes equations, and detection of gravitational waves are three seemingly unrelated scientific problems that, remarkably, can be studied from one perspective. The notion that unifies the three problems is that of ``oscillating patterns'', which are present in many natural images, help to explain nonlinear equations, and are pivotal in studying chirps and frequency-modulated signals. The first chapter of this book considers image processing, moreprecisely algorithms of image compression and denoising. This research is motivated in particular by the new standard for compression of still images known as JPEG-2000. The second chapter has new results on the Navier-Stokes and other nonlinear evolution equations. Frequency-modulated signals and theiruse in the detection of gravitational waves are covered in the final chapter. In the book, the author describes both what the oscillating patterns are and the mathematics necessary for their analysis. It turns out that this mathematics involves new properties of various Besov-type function spaces and leads to many deep results, including new generalizations of famous Gagliardo-Nirenberg and Poincare inequalities. This book is based on the ``Dean Jacqueline B. Lewis Memorial Lectures'' given bythe author at Rutgers University. It can be used either as a textbook in studying applications of wavelets to image processing or as a supplementary resource for studying nonlinear evolution equations or frequency-modulated signals. Most of the material in the book did not appear previously inmonograph literature.
Nonlinear Eigenproblems In Image Processing And Computer Vision
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Author : Guy Gilboa
language : en
Publisher: Springer
Release Date : 2018-03-29
Nonlinear Eigenproblems In Image Processing And Computer Vision written by Guy Gilboa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-29 with Computers categories.
This unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework. The text opens with an introduction to the mathematical background, together with a summary of classical variational algorithms for vision. This is followed by a focus on the foundations and applications of the new multi-scale representation based on non-linear eigenproblems. The book then concludes with a discussion of new numerical techniques for finding nonlinear eigenfunctions, and promising research directions beyond the convex case. Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processing and computer vision algorithms; describes the properties of the total variation (TV) functional, and how the concept of nonlinear eigenfunctions relate to convex functionals; provides a spectral framework for one-homogeneous functionals, and applies this framework for denoising, texture processing and image fusion; proposes novel ways to solve the nonlinear eigenvalue problem using special flows that converge to eigenfunctions; examines graph-based and nonlocal methods, for which a TV eigenvalue analysis gives rise to strong segmentation, clustering and classification algorithms; presents an approach to generalizing the nonlinear spectral concept beyond the convex case, based on pixel decay analysis; discusses relations to other branches of image processing, such as wavelets and dictionary based methods. This original work offers fascinating new insights into established signal processing techniques, integrating deep mathematical concepts from a range of different fields, which will be of great interest to all researchers involved with image processing and computer vision applications, as well as computations for more general scientific problems.
Logic Based Nonlinear Image Processing
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Author : Stephen Marshall
language : en
Publisher: SPIE Press
Release Date : 2007
Logic Based Nonlinear Image Processing written by Stephen Marshall and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
This text provides insight into the design of optimal image processing operators for implementation directly into digital hardware. Starting with simple restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications. The text is aimed principally at electronics engineers and computer scientists, but will also be of interest to anyone working with digital images.
Mathematical Methods In Time Series Analysis And Digital Image Processing
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Author : Rainer Dahlhaus
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-20
Mathematical Methods In Time Series Analysis And Digital Image Processing written by Rainer Dahlhaus 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 2007-12-20 with Computers categories.
This coherent and articulate volume summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing. The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences.
Nonlinear Image Processing
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Author :
language : en
Publisher:
Release Date : 1999
Nonlinear Image Processing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Digital filters (Mathematics) categories.
Mathematical Morphology And Its Applications To Image And Signal Processing
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Author : Petros Maragos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Mathematical Morphology And Its Applications To Image And Signal Processing written by Petros Maragos 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 morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications