Restoration of degraded images has become an important and effective tool for many technological applications like space imaging, medical imaging and many other post-processing techniques. Most of the image restoration techniques model the degradation phenomena, usually blur and noise, and then obtain an approximation of the image. Whereas, in realistic situation, one has to estimate both the true image and the blur from the degraded image characteristics in the absence of any a priori information about the blurring system. The objective of this book is to present new punctual kriging based image restoration approaches using machine-learning techniques. To achieve this objective, this book concentrates on the restoration of images corrupted with Gaussian noise by making good tradeoffs between two contradicting properties; smoothness versus edge preservation. This book makes the following contributions: Quantitative analysis of the at hand punctual kriging based image restoration techniques, applications of artificial neural networks are discussed for image denoising. Furthermore, hybrid techniques for image restoration are presented in this book.
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Asmatullah Chaudhry, Ph.D: received M.Sc. degrees in Physics and Nuclear Engineering in 1993 and 1998 from IUB and QAU, Pakistan. Further, he earned MS in 2003 and Ph.D. in 2007, from GIKI, Pakistan in Computer System Engineering, working as a Principal Scientist at PINSTECH, Pakistan. Research interests include Image Processing and Machine Learning.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Restoration of degraded images has become an important and effective tool for many technological applications like space imaging, medical imaging and many other post-processing techniques. Most of the image restoration techniques model the degradation phenomena, usually blur and noise, and then obtain an approximation of the image. Whereas, in realistic situation, one has to estimate both the true image and the blur from the degraded image characteristics in the absence of any a priori information about the blurring system. The objective of this book is to present new punctual kriging based image restoration approaches using machine-learning techniques. To achieve this objective, this book concentrates on the restoration of images corrupted with Gaussian noise by making good tradeoffs between two contradicting properties; smoothness versus edge preservation. This book makes the following contributions: Quantitative analysis of the at hand punctual kriging based image restoration techniques, applications of artificial neural networks are discussed for image denoising. Furthermore, hybrid techniques for image restoration are presented in this book. 116 pp. Englisch. Bestandsnummer des Verkäufers 9783838322681
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Restoration of degraded images has become an important and effective tool for many technological applications like space imaging, medical imaging and many other post-processing techniques. Most of the image restoration techniques model the degradation pheno. Bestandsnummer des Verkäufers 5412930
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Restoration of degraded images has become an important and effective tool for many technological applications like space imaging, medical imaging and many other post-processing techniques. Most of the image restoration techniques model the degradation phenomena, usually blur and noise, and then obtain an approximation of the image. Whereas, in realistic situation, one has to estimate both the true image and the blur from the degraded image characteristics in the absence of any a priori information about the blurring system. The objective of this book is to present new punctual kriging based image restoration approaches using machine-learning techniques. To achieve this objective, this book concentrates on the restoration of images corrupted with Gaussian noise by making good tradeoffs between two contradicting properties; smoothness versus edge preservation. This book makes the following contributions: Quantitative analysis of the at hand punctual kriging based image restoration techniques, applications of artificial neural networks are discussed for image denoising. Furthermore, hybrid techniques for image restoration are presented in this book.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. Bestandsnummer des Verkäufers 9783838322681
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Restoration of degraded images has become an important and effective tool for many technological applications like space imaging, medical imaging and many other post-processing techniques. Most of the image restoration techniques model the degradation phenomena, usually blur and noise, and then obtain an approximation of the image. Whereas, in realistic situation, one has to estimate both the true image and the blur from the degraded image characteristics in the absence of any a priori information about the blurring system. The objective of this book is to present new punctual kriging based image restoration approaches using machine-learning techniques. To achieve this objective, this book concentrates on the restoration of images corrupted with Gaussian noise by making good tradeoffs between two contradicting properties; smoothness versus edge preservation. This book makes the following contributions: Quantitative analysis of the at hand punctual kriging based image restoration techniques, applications of artificial neural networks are discussed for image denoising. Furthermore, hybrid techniques for image restoration are presented in this book. Bestandsnummer des Verkäufers 9783838322681
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Taschenbuch. Zustand: Neu. Image Processing using Punctual Kriging and Machine Learning | Applications of fuzzy logic, genetic programming and artificial neural networks in the field of Image Restoration | Asmatullah Chaudhry | Taschenbuch | 116 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838322681 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 101291314
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