Development of Some Novel Nonlinear and Adaptive Digital Image Filters for Efficient Noise Suppression

Development of Some Novel Nonlinear and Adaptive Digital Image Filters for Efficient Noise Suppression
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Some nonlinear and adaptive digital image filtering algorithms have been developed in this thesis to suppress additive white Gaussian noise (AWGN), bipolar fixed-valued impulse, also called salt and pepper noise (SPN), random-valued impulse noise (RVIN) and their combinations quite effectively. The present state-of-art technology offers high quality sensors, cameras, electronic circuitry: application specific integrated circuits (ASIC), system on chip (SOC), etc., and high quality communication channels. Therefore, the noise level in images has been reduced drastically. In literature, many efficient nonlinear image filters are found that perform well under high noise conditions. But their performance is not so good under low noise conditions as compared to the extremely high computational complexity involved therein. Thus, it is felt that there is sufficient scope to investigate and develop quite efficient but simple algorithms to suppress low-power noise in an image. When ...

Nonlinear Digital Filters

Nonlinear Digital Filters
Author: Ioannis Pitas
Publisher: Springer Science & Business Media
Total Pages: 402
Release: 2013-03-14
Genre: Technology & Engineering
ISBN: 1475760175

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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.

Handbook of Medical Imaging

Handbook of Medical Imaging
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Publisher: Academic Press
Total Pages: 983
Release: 2000-10-09
Genre: Science
ISBN: 0080533108

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In recent years, the remarkable advances in medical imaging instruments have increased their use considerably for diagnostics as well as planning and follow-up of treatment. Emerging from the fields of radiology, medical physics and engineering, medical imaging no longer simply deals with the technology and interpretation of radiographic images. The limitless possibilities presented by computer science and technology, coupled with engineering advances in signal processing, optics and nuclear medicine have created the vastly expanded field of medical imaging. The Handbook of Medical Imaging is the first comprehensive compilation of the concepts and techniques used to analyze and manipulate medical images after they have been generated or digitized. The Handbook is organized in six sections that relate to the main functions needed for processing: enhancement, segmentation, quantification, registration, visualization as well as compression storage and telemedicine. * Internationally renowned authors(Johns Hopkins, Harvard, UCLA, Yale, Columbia, UCSF) * Includes imaging and visualization * Contains over 60 pages of stunning, four-color images

IMAGE DE-NOISING TECHNIQUES: A REVIEW PAPER

IMAGE DE-NOISING TECHNIQUES: A REVIEW PAPER
Author: Sarbjit Kaur
Publisher: Infinite Study
Total Pages: 5
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A critical issue in the image restoration is the problem of de-noising images while keeping the integrity of relevant image information.

Applications of Nonlinear Adaptive Filters for Image Enhancement

Applications of Nonlinear Adaptive Filters for Image Enhancement
Author: Y. H. Lee
Publisher:
Total Pages: 4
Release: 1984
Genre:
ISBN:

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Generalizations of median filters which combine desirable properties of both linear and nonlinear filters have recently been developed by the authors. This paper gives some results of applications of these filters in the enhancement of noisy images. The authors consider in particular the median, the alpha-trimmed mean (alpha-TM), the modified trimmed mean (MTM) and the double window (DW) MTM filters. In all but the last case iterated use of the filter has been examined. The results show that the new filters (MTM and DW MTM filters) are very good for edge-preserving enhancement of images contaminated by additive noise which includes impulsive components.

Adaptive Image Processing

Adaptive Image Processing
Author: Kim-Hui Yap
Publisher: CRC Press
Total Pages: 238
Release: 2018-10-03
Genre: Technology & Engineering
ISBN: 1351834517

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Illustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI) methods and algorithms for adaptive image processing in regularization, edge detection, and early vision. With three new chapters and updated information throughout, the new edition of this popular reference includes substantial new material that focuses on applications of advanced CI techniques in image processing applications. It introduces new concepts and frameworks that demonstrate how neural networks, support vector machines, fuzzy logic, and evolutionary algorithms can be used to address new challenges in image processing, including low-level image processing, visual content analysis, feature extraction, and pattern recognition. Emphasizing developments in state-of-the-art CI techniques, such as content-based image retrieval, this book continues to provide educators, students, researchers, engineers, and technical managers in visual information processing with the up-to-date understanding required to address contemporary challenges in image content processing and analysis.

Intelligent and Adaptive Systems in Medicine

Intelligent and Adaptive Systems in Medicine
Author: Olivier C. L. Haas
Publisher: CRC Press
Total Pages: 402
Release: 2008-03-19
Genre: Medical
ISBN: 1420012088

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Intelligent and adaptive techniques are rapidly being used in all stages of medical treatment, from the initial diagnosis to planning delivery and follow-up therapy.To realize the full potential of these techniques, developers and end users must understand both the underlying technology and the specifics of the medical application considered. Focus

Neural Information Processing. Models and Applications

Neural Information Processing. Models and Applications
Author: Kevin K.W. Wong
Publisher: Springer
Total Pages: 763
Release: 2010-11-18
Genre: Computers
ISBN: 3642175341

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The two volume set LNCS 6443 and LNCS 6444 constitutes the proceedings of the 17th International Conference on Neural Information Processing, ICONIP 2010, held in Sydney, Australia, in November 2010. The 146 regular session papers presented were carefully reviewed and selected from 470 submissions. The papers of part I are organized in topical sections on neurodynamics, computational neuroscience and cognitive science, data and text processing, adaptive algorithms, bio-inspired algorithms, and hierarchical methods. The second volume is structured in topical sections on brain computer interface, kernel methods, computational advance in bioinformatics, self-organizing maps and their applications, machine learning applications to image analysis, and applications.