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Co-registration of Satellite Images Based on Invariant Local Features

Tahoun, Mohamed and El Rahman Shabayek, Abd and Reulke, Ralf and Hassanien, AboulElla (2015) Co-registration of Satellite Images Based on Invariant Local Features. In: Intelligent Systems'2014. Intelligent Systems Advances in Intelligent Systems and Computing, 323. Springer International Publishing. pp. 653-660. ISBN 978-3-319-11309-8. ISSN 2194-5357

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Official URL: http://dx.doi.org/10.1007/978-3-319-11310-4_56

Abstract

Detection and matching of features from satellite images taken from different sensors, viewpoints, or at different times are important tasks when manipulating and processing remote sensing data for many applications. This paper presents a scheme for satellite image co-registration using invariant local features. Different corner and scale based feature detectors have been tested during the keypoint extraction, descriptor construction and matching processes. The framework suggests a sub-sampling process which controls the number of extracted key points for a real time processing and for minimizing the hardware requirements. After getting the pairwise matches between the input images, a full registration process is followed by applying bundle adjustment and image warping then compositing the registered version. Harris and GFTT have recorded good results with ASTER images while both with SURF give the most stable performance on optical images in terms of better inliers ratios and running time compared to the other detectors. SIFT detector has recorded the best inliers ratios on TerraSAR-X data while it still has a weak performance with other optical images like Rapid-Eye and ASTER.

Item URL in elib:https://elib.dlr.de/95037/
Document Type:Book Section
Title:Co-registration of Satellite Images Based on Invariant Local Features
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Tahoun, MohamedDepartment of Computer Science, FCI, Suez Canal University, Ismailia, EgyptUNSPECIFIED
El Rahman Shabayek, AbdDepartment of Computer Science, FCI, Suez Canal University, Ismailia, EgyptUNSPECIFIED
Reulke, RalfInstitut für Optische SensorsystemeUNSPECIFIED
Hassanien, AboulEllaDepartment of Information Technology, FCI, Cairo university, Cairo, EgyptUNSPECIFIED
Date:2015
Journal or Publication Title:Intelligent Systems
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:323
DOI :10.1007/978-3-319-11310-4_56
Page Range:pp. 653-660
Editors:
EditorsEmail
Filev, D.Ford Motor Company, Research & Advanced Engineering
Publisher:Springer International Publishing
Series Name:Advances in Intelligent Systems and Computing
ISSN:2194-5357
ISBN:978-3-319-11309-8
Status:Published
Keywords:SURF; SIFT; GFTT; feature extraction and matching; satellite image co-registration
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Optische Sensorik - Theorie, Kalibration, Verifikation
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Optical Sensor Systems > Optics, Calibration and Validation
Deposited By: Reulke, Prof. Dr. Ralf
Deposited On:09 Feb 2015 07:16
Last Modified:09 Feb 2015 07:16

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