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Image Processing using Punctual Kriging and Machine Learning: Applications of fuzzy logic, genetic programming and artificial neural networks in the field of Image Restoration - Couverture souple

 
9783838322681: Image Processing using Punctual Kriging and Machine Learning: Applications of fuzzy logic, genetic programming and artificial neural networks in the field of Image Restoration

Synopsis

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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Présentation de l'éditeur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

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Etat : 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. N° de réf. du vendeur 5412930

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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783838322681

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Asmatullah Chaudhry
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783838322681

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Taschenbuch. Etat : Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch. N° de réf. du vendeur 9783838322681

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