Authors:
- Provides in-depth coverage of novel computer vision methods for remote sensing applications
- Includes end-of-chapter summaries and review questions
- With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (13 chapters)
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Front Matter
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Sensors
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Front Matter
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Introduction
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Sensors
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Front Matter
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The Multispectral Information
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Front Matter
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Extracting Residential Regions
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Front Matter
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Building and Road Detection
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Front Matter
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Summarizing the Overall System
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Front Matter
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About this book
Reviews
From the reviews:
“The authors write that their aims were the proposal of a novel automated end-to-end system to analyze multispectral satellite images and to emphasize how many research problems in remote sensing applications are waiting to be solved by the computer vision community. Well, the book satisfies both these goals. … it represents a good reference book, even a milestone, for teaching multispectral image understanding to students and/or young researchers.” (Primo Zingaretti, IAPR Newsletter, Vol. 34 (3), July-August, 2012)Authors and Affiliations
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Electrical and Electronics Engineering, Yeditepe University, Kayisdagi, Turkey
Cem Ünsalan
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Dept. Electrical, Comp. & Systems Eng., Rensselaer Polytechnic Institute, Troy, USA
Kim L. Boyer
Bibliographic Information
Book Title: Multispectral Satellite Image Understanding
Book Subtitle: From Land Classification to Building and Road Detection
Authors: Cem Ünsalan, Kim L. Boyer
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-0-85729-667-2
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London Limited 2011
Hardcover ISBN: 978-0-85729-666-5Published: 20 May 2011
Softcover ISBN: 978-1-4471-2656-0Published: 15 July 2013
eBook ISBN: 978-0-85729-667-2Published: 18 May 2011
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XVIII, 186
Topics: Image Processing and Computer Vision, Pattern Recognition