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Object Detection in Satellite and Aerial Images: Remote Sensing Applications

Sirmacek, Beril and Ünsalan, Cem (2010) Object Detection in Satellite and Aerial Images: Remote Sensing Applications. VDM Verlag Dr. Müller. ISBN 3639269322.

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Official URL: http://www.amazon.com/Object-Detection-Satellite-Aerial-Images/dp/3639269322/ref=sr_1_1?ie=UTF8&s=books&qid=1277744006&sr=8-1


Very high resolution satellite and aerial images provide valuable information to researchers. With their availability, there has been much interest to extract man-made objects from such imagery. Among these, detection of objects such as buildings, road segments, and urban area boundaries play crucial roles especially for municipalities, government agencies, rescue teams, military, and other civil agencies. For a human expert, manually extracting this valuable information is tedious and prone to errors. Therefore, advanced object detection algorithms should be developed to detect objects from remotely sensed images automatically. This book provides some examples for these advanced algorithms, with particular emphasis on urban region, building and road detection topics.

Document Type:Book
Title:Object Detection in Satellite and Aerial Images: Remote Sensing Applications
AuthorsInstitution or Email of Authors
Sirmacek, BerilBeril.Sirmacek@dlr.de
Ünsalan, Cemünsalan@yeditepe.edu.tr
Date:23 June 2010
Page Range:pp. 1-168
Publisher:VDM Verlag Dr. Müller
Keywords:satellite images, building detection, road detection, urban region detection, aerial images, object detection,
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Photogrammetrie und Bildanalyse (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Beril Sirmacek
Deposited On:30 Jun 2010 08:41
Last Modified:12 Dec 2013 20:58

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