Blind deconvolution (40 Ergebnisse)

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Sprache: Englisch
Verlag: Wiley-Interscience. 2000
Serie: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control, Buch 13 von 33. Buch 13 von 33 - Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
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Volume 2. 16 x 24 cm. 200 pages. HC Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

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Zustand: New. KlappentextrnrnExcerpt from Apex Blind Deconvolution of Color Hubble Space Telescope Imagery and Other Astronomical DataIn recent years. Much excellent work has been done in the area of blind deconvolution of astronomical data.4 11 Many .

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Zustand: New. KlappentextrnrnThe purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The p.

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Zustand: New. KlappentextrnrnThis research presents an algorithm that improves the ability to view objects using an electro-optical imaging system withat least one polarization sensitive channel in addition tothe primary channel. An innovative algorithm for d.

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Zustand: New. KlappentextrnrnCoherent imaging systems offer unique benefits to system operators in terms of resolving power, range gating, selective illumination and utility for applications where passively illuminated targets have limited emissivity or refle.

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Blind Image Deconvolution: Methods and Convergence
Chaudhuri, Subhasis (Author)/ Velmurugan, Rajbabu (Author)/ Rameshan, Renu (Author)
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Sprache: Englisch
Verlag: British Library, Historical Print Editions Nov 2012 2012
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Taschenbuch. Zustand: Neu. Neuware - The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one… polarized image, in a GEM algorithm to reconstruct the object. Long exposure images were simulated and a smile Kolmogorov model used. This allowed for the atmosphere to be characterized by single parameter, the Fried Parameter. Introducing a novel polarization prior that restricts the polarization parameter, it was possible to determine the Fried Parameter to within half a centimeter without any addition knowledge or processes. It was also found that when a high polarization diversity was present in the image could be reconstructed with significantly better resolution and signal level did not affect this resolving capability. At very low signal levels, imagery with low to no diversity could not be resolved at all whereas high diversity resolved equally as well as if there was a high signal level.

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Taschenbuch. Zustand: Neu. Neuware - Images are used for both aerial and space imagery applications, including target detection and tracking. The current problem concerning objects in geosynchronous orbit is that they are dim and hard to resolve because of their distance. This work will further the combined effort of AFIT and AF…RL to provide enhanced space situational awareness (SSA) and space surveillance. SSA is critical in a time when many countries possess the technology to put satellites into orbit. Enhanced imaging technology improves the Air Force's ability to see if foreign satellites or other space hardware are operating in the vicinity of our own assets at geosynchronous orbit. Image deblurring or denoising is a crucial part of restoring images that have been distorted either by movement during the capture process, using out-of-focus optics, or atmospheric turbulence. The goal of this work is to develop a new blind deconvolution method for imaging objects at geosynchronous orbit. It will feature an expectation maximization (EM) approach to iteratively deblur an image while using the convergence of the image's variance as the stopping criteria.

Sprache: Englisch
Verlag: British Library, Historical Print Editions Dez 2012 2012
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Taschenbuch. Zustand: Neu. Neuware - This research presents an algorithm that improves the ability to view objects using an electro-optical imaging system withat least one polarization sensitive channel in addition tothe primary channel. An innovative algorithm for detection and estimation of the defocus aberration present in an… image is also developed. Using a known defocus aberration, an iterative polarimeter deconvolution algorithm is developed using a generalized expectation-maximization (GEM) model. The polarimeter deconvolution algorithm is extended to an iterative polarimeter multiframe blind deconvolution (PMFBD) algorithm with an unknown aberration. Using both simulated and laboratory images, the results of the new PMFBD algorithm clearly outperforms an RL-based MFBD algorithm. The convergence rate is significantly faster with better fidelity of reproduction of the targets. Clearly, leveraging polarization data in electro-optical imaging systems has the potential to significantly improve the ability to resolve objectsand, thus, improve Space Situation Awareness.

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Taschenbuch. Zustand: Neu. Neuware - Coherent imaging systems offer unique benefits to system operators in terms of resolving power, range gating, selective illumination and utility for applications where passively illuminated targets have limited emissivity or reflectivity. In contrast to incoherent imaging systems, partially c…oherent illumination causes difficulty during image processing due to high levels of image speckle caused by constructive and de- structive interference effects unique to the highly coherent illumination source. Image speckle is caused by the random phase delays that occur due to target roughness and the turbulent atmosphere between the remote target and optical system. To combat such effects, a number of short-exposure images are combined by incoherent averaging to arrive at an image that has greatly decreased levels of speckle. Unfortunately, such average images suffer from decreased spatial resolution due to blur resulting from atmospheric distortion. Effective image restoration may be realized by inverse filtering the recovered average image with an optical transfer function that describes the overall optical system and atmospheric turbulence. In cases where it is inconvenient or impossible to measure the parameters of this evolving function, blind deconvolution algorithms may be applied to estimate both the unknown remote scene reflectance, as well as the unknown system transfer function. This research proposes a novel blind deconvolution algorithm that is based on a maximum a posteriori Bayesian estimator constructed upon a physically-based statistical model for the intensity of the partially coherent light at the imaging detector. The estimator is initially constructed using a shift- invariant system model, and is later extended to the case of a shift-variant optical system by the addition of a transfer function term that quantifies optical blur for given field-of-views and atmospheric conditions. The estimators are evaluated using both synthetically generated imagery.

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Buch. Zustand: Neu. Neuware - Images are used for both aerial and space imagery applications, including target detection and tracking. The current problem concerning objects in geosynchronous orbit is that they are dim and hard to resolve because of their distance. This work will further the combined effort of AFIT and AFRL to p…rovide enhanced space situational awareness (SSA) and space surveillance. SSA is critical in a time when many countries possess the technology to put satellites into orbit. Enhanced imaging technology improves the Air Force's ability to see if foreign satellites or other space hardware are operating in the vicinity of our own assets at geosynchronous orbit. Image deblurring or denoising is a crucial part of restoring images that have been distorted either by movement during the capture process, using out-of-focus optics, or atmospheric turbulence. The goal of this work is to develop a new blind deconvolution method for imaging objects at geosynchronous orbit. It will feature an expectation maximization (EM) approach to iteratively deblur an image while using the convergence of the image's variance as the stopping criteria.

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Taschenbuch. Zustand: Neu. Image Deblurring Using Blind Deconvolution | Charu Jain (u. a.) | Taschenbuch | 56 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139457007 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Sprache: Englisch
Verlag: Wiley-Interscience 2000
Serie: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control, Buch 13 von 33. Buch 13 von 33 - Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
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Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Blind deconvolution is a classical image processing problem which has been investigated by a large number of researchers over the last four decades. The purpose of this monograph is not to propose yet another method for blind image restoration. Rathe…r the basic issue of deconvolvability has been explored from a theoretical view point. Some authors claim very good results while quite a few claim that blind restoration does not work. The authors clearly detail when such methods are expected to work and when they will not.In order to avoid the assumptions needed for convergence analysis in the Fourier domain, the authors use a general method of convergence analysis used for alternate minimization based on three point and four point properties of the points in the image space. The authors prove that all points in the image space satisfy the three point property and also derive the conditions under which four point property is satisfied. This provides the conditions under which alternate minimization for blind deconvolution converges with a quadratic prior.Since the convergence properties depend on the chosen priors, one should design priors that avoid trivial solutions. Hence, a sparsity based solution is also provided for blind deconvolution, by using image priors having a cost that increases with the amount of blur, which is another way to prevent trivial solutions in joint estimation. This book will be a highly useful resource to the researchers and academicians in the specific area of blind deconvolution.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Blind deconvolution is a classical image processing problem which has been investigated by a large number of researchers over the last four decades. The purpose of this monograph is not to propose yet another method for blind image restoration. Rather the b…asic issue of deconvolvability has been explored from a theoretical view point. Some authors claim very good results while quite a few claim that blind restoration does not work. The authors clearly detail when such methods are expected to work and when they will not.In order to avoid the assumptions needed for convergence analysis in the Fourier domain, the authors use a general method of convergence analysis used for alternate minimization based on three point and four point properties of the points in the image space. The authors prove that all points in the image space satisfy the three point property and also derive the conditions under which four point property is satisfied. This provides the conditions under which alternate minimization for blind deconvolution converges with a quadratic prior.Since the convergence properties depend on the chosen priors, one should design priors that avoid trivial solutions. Hence, a sparsity based solution is also provided for blind deconvolution, by using image priors having a cost that increases with the amount of blur, which is another way to prevent trivial solutions in joint estimation. This book will be a highly useful resource to the researchers and academicians in the specific area of blind deconvolution.

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Taschenbuch. Zustand: Neu. Blind Image Deconvolution | Methods and Convergence | Subhasis Chaudhuri (u. a.) | Taschenbuch | xv | Englisch | 2016 | Springer | EAN 9783319352169 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preig…u.

Sprache: Englisch
Verlag: Wiley 2000
Serie: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control, Buch 13 von 33. Buch 13 von 33 - Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
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Zustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | A complete, one-stop reference on the state of the art of unsupervised adaptive filtering While unsupervised adaptive filtering has its roots in the 1960s, more recent advances in signal processing, information theory, imaging, and remote sensing have made thi…s a hot area for research in several diverse fields. This book brings together cutting-edge information previously available only in disparate papers and articles, presenting a thorough and integrated treatment of the two major classes of algorithms used in the field, namely, blind signal separation and blind channel equalization algorithms. Divided into two volumes for ease of presentation, this important work shows how these algorithms, although developed independently, are closely related foundations of unsupervised adaptive filtering. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications in diverse fields. More than 100 illustrations as well as case studies, appendices, and references further enhance this excellent resource. Following coverage begun in Volume I: Blind Source Separation, this volume discusses: * The core of FSE-CMA behavior theory * Relationships between blind deconvolution and blind source separation * Blind separation of independent sources based on multiuser kurtosis optimization criteria.