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Book An Introduction to Nonlinear Image Processing

Download or read book An Introduction to Nonlinear Image Processing written by Edward R. Dougherty and published by SPIE Press. This book was released on 1994 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Nonlinear Image Processing

Download or read book Nonlinear Image Processing written by Sanjit Mitra and published by Academic Press. This book was released on 2001 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Mathematical Nonlinear Image Processing

Download or read book Mathematical Nonlinear Image Processing written by Edward R. Dougherty and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).

Book Nonlinear Eigenproblems in Image Processing and Computer Vision

Download or read book Nonlinear Eigenproblems in Image Processing and Computer Vision written by Guy Gilboa and published by Springer. This book was released on 2018-03-29 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Introduction to Image Processing

Download or read book Introduction to Image Processing written by André Marion and published by Springer. This book was released on 2013-11-11 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: I. The past. the present . . . and the future It is possible to take the view that ever since it began, the "ancient" branch of physics known as Optics has been concerned with process ing images. But since the Nineteen-Thirties increasingly close ties have been forming between Optics, which until then had been largely based on instruments, and the sciences of communication and infor mation arising out of mathematics and electronics. Such developments follow naturally, since communication systems and image-forming systems are all designed to receive or transmit information. Further more the same mathematical forms are used for describing the beha viour of electrical and optical systems. It is a question of systems theory, particularly linear systems, and of Fourier's analysis methods, which together constitute an important part of Signal Theory. In the case of communication systems carrying signals of an electrical nature, information is time-related or temporal. Transmitted signals are one-dimensional and functions of a single variable, time t. In the case of optical systems information is spatial in nature. Signals are distributions of light intensity in space. In general they are treated as two-dimensional signals, being functions of two spatia! variables written as x and y. In the early Fifties the way forward became clearer still when some scientists at the Institut d'Optique in Paris began using optical filtering techniques in coherent light in order to enhance the quality of photographs.

Book Nonlinear Image Processing II

Download or read book Nonlinear Image Processing II written by and published by . This book was released on 1991 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonlinear Digital Filtering with Python

Download or read book Nonlinear Digital Filtering with Python written by Ronald K. Pearson and published by CRC Press. This book was released on 2018-09-03 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Digital Filtering with Python: An Introduction discusses important structural filter classes including the median filter and a number of its extensions (e.g., weighted and recursive median filters), and Volterra filters based on polynomial nonlinearities. Adopting both structural and behavioral approaches in characterizing and designing nonlinear digital filters, this book: Begins with an expedient introduction to programming in the free, open-source computing environment of Python Uses results from algebra and the theory of functional equations to construct and characterize behaviorally defined nonlinear filter classes Analyzes the impact of a range of useful interconnection strategies on filter behavior, providing Python implementations of the presented filters and interconnection strategies Proposes practical, bottom-up strategies for designing more complex and capable filters from simpler components in a way that preserves the key properties of these components Illustrates the behavioral consequences of allowing recursive (i.e., feedback) interconnections in nonlinear digital filters while highlighting a challenging but promising research frontier Nonlinear Digital Filtering with Python: An Introduction supplies essential knowledge useful for developing and implementing data cleaning filters for dynamic data analysis and time-series modeling.

Book Nonlinear Signal Processing

Download or read book Nonlinear Signal Processing written by Gonzalo R. Arce and published by John Wiley & Sons. This book was released on 2005-01-03 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which emerge from statistical estimation principles, and where the underlying signals are non-Gaussian, rather than Gaussian, processes. Notably, by concentrating on just two non-Gaussian models, a large set of tools is developed that encompass a large portion of the nonlinear signal processing tools proposed in the literature over the past several decades. Key features include: * Numerous problems at the end of each chapter to aid development and understanding * Examples and case studies provided throughout the book in a wide range of applications bring the text to life and place the theory into context * A set of 60+ MATLAB software m-files allowing the reader to quickly design and apply any of the nonlinear signal processing algorithms described in the book to an application of interest is available on the accompanying FTP site.

Book Nonlinear Digital Filters

Download or read book Nonlinear Digital Filters written by Ioannis Pitas and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: The function of a filter is to transform a signal into another one more suit able for a given purpose. As such, filters find applications in telecommunica tions, radar, sonar, remote sensing, geophysical signal processing, image pro cessing, and computer vision. Numerous authors have considered deterministic and statistical approaches for the study of passive, active, digital, multidimen sional, and adaptive filters. Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now available. Our research interests in this area created opportunity for cooperation and co authored publications during the past few years in many nonlinear filter families described in this book. As a result of this cooperation and a visit from John Pitas on a research leave at the University of Toronto in September 1988, the idea for this book was first conceived. The difficulty in writing such a mono graph was that the area seemed fragmented and no general theory was available to encompass the many different kinds of filters presented in the literature. However, the similarities of some families of nonlinear filters and the need for such a monograph providing a broad overview of the whole area made the pro ject worthwhile. The result is the book now in your hands, typeset at the Department of Electrical Engineering of the University of Toronto during the summer of 1989.

Book An Introduction to Nonlinear Functional Analysis and Elliptic Problems

Download or read book An Introduction to Nonlinear Functional Analysis and Elliptic Problems written by Antonio Ambrosetti and published by Springer Science & Business Media. This book was released on 2011-07-19 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained textbook provides the basic, abstract tools used in nonlinear analysis and their applications to semilinear elliptic boundary value problems and displays how various approaches can easily be applied to a range of model cases. Complete with a preliminary chapter, an appendix that includes further results on weak derivatives, and chapter-by-chapter exercises, this book is a practical text for an introductory course or seminar on nonlinear functional analysis.

Book Nonlinear Image Processing X

Download or read book Nonlinear Image Processing X written by and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonlinear Image Processing

Download or read book Nonlinear Image Processing written by and published by . This book was released on 1999 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Medical Image Analysis Methods

Download or read book Medical Image Analysis Methods written by Lena Costaridou and published by CRC Press. This book was released on 2005-07-13 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: To successfully detect and diagnose disease, it is vital for medical diagnosticians to properly apply the latest medical imaging technologies. It is a worrisome reality that due to either the nature or volume of some of the images provided, early or obscured signs of disease can go undetected or be misdiagnosed. To combat these inaccuracies, diagno

Book Encyclopedia of Optical Engineering  Abe Las  pages 1 1024

Download or read book Encyclopedia of Optical Engineering Abe Las pages 1 1024 written by Ronald G. Driggers and published by CRC Press. This book was released on 2003 with total page 1240 pages. Available in PDF, EPUB and Kindle. Book excerpt: PRINT/ONLINE PRICING OPTIONS AVAILABLE UPON REQUEST [email protected]

Book Analysis of Sampled Imaging Systems

Download or read book Analysis of Sampled Imaging Systems written by Richard H. Vollmerhausen and published by SPIE Press. This book was released on 2000 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in solid state detector arrays, flat panel displays and digital image processing have prompted an increasing variety of sampled imaging products and possibilities. These technology developments provide new opportunities and problems for the design engineer and system analyst - this tutorial's intended reader.

Book Logic based Nonlinear Image Processing

Download or read book Logic based Nonlinear Image Processing written by Stephen Marshall and published by SPIE Press. This book was released on 2007 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Nonlinear Digital Filters

Download or read book Nonlinear Digital Filters written by W. K. Ling and published by Academic Press. This book was released on 2010-07-27 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters. It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time systems, such as sigma delta modulators, digital phase lock loops, and turbo coders. It uses new methods based on symbolic dynamics, enabling the engineer to easily operate reliable nonlinear digital filters. It gives practical, 'real-world' applications of nonlinear digital filters and contains many examples. The book is ideal for professional engineers working with signal processing applications, as well as advanced undergraduates and graduates conducting a nonlinear filter analysis project. Uses new methods based on symbolic dynamics, enabling the engineer more easily to operate reliable nonlinear digital filters Gives practical, "real-world" applications of nonlinear digital filter Includes many examples.