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Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection - Couverture rigide
Synopsis
This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.
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- ÉditeurSpringer London Ltd
- Date d'édition2011
- ISBN 10 0857296663
- ISBN 13 9780857296665
- ReliureRelié
- Langueanglais
- Nombre de pages186
- Coordonnées du fabricantnon disponible
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Multispectral Satellite Image Understanding : From Land Classification to Building and Road Detection
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Springer London, 2011
ISBN 10 : 0857296663
ISBN 13 : 9780857296665
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Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut - Neubindung, Buchschnitt leicht verkürzt, Buchrücken leicht angestoßen, Ausgabe 2011 | Seiten: 204 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 10541344/12
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Multispectral Satellite Image Understanding
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides in-depth coverage of novel computer vision methods for remote sensing applicationsIncludes end-of-chapter summaries and review questionsWith a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace CenterThis book pre. N° de réf. du vendeur 5979381
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Multispectral Satellite Image Understanding
Edité par
Springer London Mai 2011, 2011
ISBN 10 : 0857296663
ISBN 13 : 9780857296665
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data. However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing.This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features:With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace CenterProvides end-of-chapter summaries and review questionsPresents a detailed review on remote sensing satellitesExamines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indicesInvestigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic imagesAddresses the problem of detecting residential regionsDescribes a house and street network-detection subsystemConcludes with a summary of the key ideas covered in the bookThis pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities. Urban planners and policy makers will also find considerable value in the proposed system.Dr. Cem Ünsalan is an Associate Professor in the Department of Electrical and Electronics Engineering at Yeditepe University, Istanbul, Turkey. Dr. Kim Boyer is Professor and Head of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA. 204 pp. Englisch. N° de réf. du vendeur 9780857296665
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Multispectral Satellite Image Understanding : From Land Classification to Building and Road Detection
Edité par
Springer London, Springer London, 2011
ISBN 10 : 0857296663
ISBN 13 : 9780857296665
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data. However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing.This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features:With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace CenterProvides end-of-chapter summaries and review questionsPresents a detailed review on remote sensing satellitesExamines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indicesInvestigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic imagesAddresses the problem of detecting residential regionsDescribes a house and street network-detection subsystemConcludes with a summary of the key ideas covered in the bookThis pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities. Urban planners and policy makers will also find considerable value in the proposed system.Dr. Cem Ünsalan is an Associate Professor in the Department of Electrical and Electronics Engineering at Yeditepe University, Istanbul, Turkey. Dr. Kim Boyer is Professor and Head of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA. N° de réf. du vendeur 9780857296665
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Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Etat : New. In. N° de réf. du vendeur ria9780857296665_new
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Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection
Edité par
Springer London Ltd, 2011
ISBN 10 : 0857296663
ISBN 13 : 9780857296665
Neuf
Couverture rigide
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Hardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 468. N° de réf. du vendeur C9780857296665
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Multispectral Satellite Image Understanding
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 204. N° de réf. du vendeur 263620819
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Multispectral Satellite Image Understanding
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. pp. 204 63 Illus. (27 Col.). N° de réf. du vendeur 4227084
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Multispectral Satellite Image Understanding
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. pp. 204. N° de réf. du vendeur 183620825
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Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Etat : New. N° de réf. du vendeur ABLIING23Mar2317530013227
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