Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: Revaluation Books, Exeter, Regno Unito
EUR 63,66
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Aggiungi al carrelloPaperback. Condizione: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Image Fusion Using HOSVD | Suchita Hatte | Taschenbuch | 64 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659934537 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP Lambert Academic Publishing Sep 2016, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The goal of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains as much information from all the source images as possible.There are many image fusion methods.This book present some of the image fusion techniques for image fusion and propose novel higher order singular value decomposition (HOSVD) based image fusion algorithm. Image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing the divided subtensors rather than the whole tensor. 64 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hatte SuchitaProf. Hatte Suchita Chandrakant from the Electronics Department, K.B.P. College of engineering, Satara. She is Currently working in K.B.P. College of engineering as an associate professor.The goal of image fusion is .
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Aug 2016, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The goal of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains as much information from all the source images as possible.There are many image fusion methods.This book present some of the image fusion techniques for image fusion and propose novel higher order singular value decomposition (HOSVD) based image fusion algorithm. Image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing the divided subtensors rather than the whole tensor.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2016
ISBN 10: 3659934534 ISBN 13: 9783659934537
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains as much information from all the source images as possible.There are many image fusion methods.This book present some of the image fusion techniques for image fusion and propose novel higher order singular value decomposition (HOSVD) based image fusion algorithm. Image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing the divided subtensors rather than the whole tensor.