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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. doi: 10.1007/978-3-319-11310-4_56. 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


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
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Tahoun, MohamedDepartment of Computer Science, FCI, Suez Canal University, Ismailia, EgyptUNSPECIFIEDUNSPECIFIED
El Rahman Shabayek, AbdDepartment of Computer Science, FCI, Suez Canal University, Ismailia, EgyptUNSPECIFIEDUNSPECIFIED
Reulke, RalfInstitut für Optische SensorsystemeUNSPECIFIEDUNSPECIFIED
Hassanien, AboulEllaDepartment of Information Technology, FCI, Cairo university, Cairo, EgyptUNSPECIFIEDUNSPECIFIED
Journal or Publication Title:Intelligent Systems
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 653-660
EditorsEmailEditor's ORCID iDORCID Put Code
Filev, D.Ford Motor Company, Research & Advanced EngineeringUNSPECIFIEDUNSPECIFIED
Publisher:Springer International Publishing
Series Name:Advances in Intelligent Systems and Computing
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 - Earth Observation
DLR - Research theme (Project):R - Vorhaben Optische Sensorik - Theorie, Kalibration, Verifikation (old)
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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