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Nonlinear Filters For Image Processing
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Author :Edward R. Dougherty Publisher :SPIE-International Society for Optical Engineering ISBN 13 :9780819430335 Total Pages :0 pages Book Rating :4.4/5 (33 download)
Book Synopsis Nonlinear Filters for Image Processing by : Edward R. Dougherty
Download or read book Nonlinear Filters for Image Processing written by Edward R. Dougherty and published by SPIE-International Society for Optical Engineering. This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonlinear Image Processing by : Giovanni Sicuranza
Download or read book Nonlinear Image Processing written by Giovanni Sicuranza and published by Elsevier. This book was released on 2000-09-15 with total page 478 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. - Presents the latest developments in a variety of filter design techniques and algorithms - Contains essential information for development of Human Vision Systems (HVS) - Provides foundations for digital imaging and image capture technology
Book Synopsis Nonlinear Digital Filters by : Ioannis Pitas
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 Synopsis Nonlinear Image Processing by : Sanjit Mitra
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 Synopsis Nonlinear Digital Filters by : W. K. Ling
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.
Book Synopsis Nonlinear Digital Filtering with Python by : Ronald K. Pearson
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 298 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 Synopsis Hands-On Image Processing with Python by : Sandipan Dey
Download or read book Hands-On Image Processing with Python written by Sandipan Dey and published by Packt Publishing Ltd. This book was released on 2018-11-30 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.
Book Synopsis Complex Valued Nonlinear Adaptive Filters by : Danilo P. Mandic
Download or read book Complex Valued Nonlinear Adaptive Filters written by Danilo P. Mandic and published by John Wiley & Sons. This book was released on 2009-04-20 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.
Book Synopsis An Introduction to Nonlinear Image Processing by : Edward R. Dougherty
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 Synopsis Mathematical Nonlinear Image Processing by : Edward R. Dougherty
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 Synopsis Digital Image Processing Methods by : Dougherty
Download or read book Digital Image Processing Methods written by Dougherty and published by CRC Press. This book was released on 2020-08-26 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique reference presents in-depth coverage of the latest methods and applications of digital image processing describing various computer architectures ideal for satisfying specific image processing demands.
Book Synopsis The Essential Guide to Image Processing by : Alan C. Bovik
Download or read book The Essential Guide to Image Processing written by Alan C. Bovik and published by Academic Press. This book was released on 2009-07-08 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to the basic and intermediate concepts of image processing from the leading people in the field Up-to-date content, including statistical modeling of natural, anistropic diffusion, image quality and the latest developments in JPEG 2000 This comprehensive and state-of-the art approach to image processing gives engineers and students a thorough introduction, and includes full coverage of key applications: image watermarking, fingerprint recognition, face recognition and iris recognition and medical imaging. "This book combines basic image processing techniques with some of the most advanced procedures. Introductory chapters dedicated to general principles are presented alongside detailed application-orientated ones. As a result it is suitably adapted for different classes of readers, ranging from Master to PhD students and beyond." – Prof. Jean-Philippe Thiran, EPFL, Lausanne, Switzerland "Al Bovik’s compendium proceeds systematically from fundamentals to today’s research frontiers. Professor Bovik, himself a highly respected leader in the field, has invited an all-star team of contributors. Students, researchers, and practitioners of image processing alike should benefit from the Essential Guide." – Prof. Bernd Girod, Stanford University, USA "This book is informative, easy to read with plenty of examples, and allows great flexibility in tailoring a course on image processing or analysis." – Prof. Pamela Cosman, University of California, San Diego, USA A complete and modern introduction to the basic and intermediate concepts of image processing – edited and written by the leading people in the field An essential reference for all types of engineers working on image processing applications Up-to-date content, including statistical modelling of natural, anisotropic diffusion, image quality and the latest developments in JPEG 2000
Book Synopsis Medical Imaging Systems by : Andreas Maier
Download or read book Medical Imaging Systems written by Andreas Maier and published by Springer. This book was released on 2018-08-02 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.
Book Synopsis Logic-based Nonlinear Image Processing by : Stephen Marshall
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 Synopsis Nonlinear Signal and Image Processing by : Kenneth E. Barner
Download or read book Nonlinear Signal and Image Processing written by Kenneth E. Barner and published by CRC Press. This book was released on 2003-11-24 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical. This book details recent advances in nonl
Book Synopsis Fuzzy Techniques in Image Processing by : Etienne E. Kerre
Download or read book Fuzzy Techniques in Image Processing written by Etienne E. Kerre and published by Physica. This book was released on 2013-03-19 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since time immemorial, vision in general and images in particular have played an important and essential role in human life. Nowadays, the field of image processing also has numerous scientific, commercial, industrial and military applications. All these applications result from the interaction between fun damental scientific research on the one hand, and the development of new and high-standard technology on the other hand. Regarding the scientific com ponent, quite recently the scientific community became familiar with "fuzzy techniques" in image processing, which make use of the framework of fuzzy sets and related theories. The theory of fuzzy sets was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from membership to nonmembership, providing partial degrees of member ship. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. With this vol ume, we want to demonstrate that the introduction and application of fuzzy techniques can also be very successful in the area of image processing. This book contains high-quality contributions of over 30 field experts, covering a wide range of both theoretical and practical applications of fuzzy techniques in image processing.
Book Synopsis Fuzzy Filters for Image Processing by : Mike Nachtegael
Download or read book Fuzzy Filters for Image Processing written by Mike Nachtegael and published by Springer. This book was released on 2013-06-05 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ongoing increase in scale of integration of electronics makes storage and computational power affordable to many applications. Also image process ing systems can benefit from this trend. A variety of algorithms for image processing tasks becomes close at hand. From the whole range of possible approaches, those based on fuzzy logic are the ones this book focusses on. A particular useful property of fuzzy logic techniques is their ability to represent knowledge in a way which is comprehensible to human interpretation. The theory of fuzzy sets and fuzzy logic was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from mem bership to nonmembership, providing partial degrees of membership. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. The present book resulted from the workshop "Fuzzy Filters for Image Processing" which was organized at the 10th FUZZ-IEEE Conference in Mel bourne, Australia. At this event several speakers have given an overview of the current state-of-the-art of fuzzy filters for image processing. Afterwards, the book has been completed with contributions of other international re searchers.
