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A Framework for Benchmarking of Feature Extraction Methods in Earth Observation image Analysis

Georgescu, Florin-Andrei and Vaduva, Corina and Datcu, Mihai and Răducanu, Dan (2014) A Framework for Benchmarking of Feature Extraction Methods in Earth Observation image Analysis. In: Proceedings of ESA-EUSC-JRC 2014 - 9th Conference on Image Information Mining Conference: The Sentinels Era, pp. 81-84. EU. ESA-EUSC-JRC 2014, 05-07 March 2014, Bucharest, Romania. DOI: 10.2788/25852 ISBN 978-92-79-36160-9 ISSN 1831-9424

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Official URL: http://bookshop.europa.eu/en/proceedings-of-9th-esa-eusc-jrc-conference-on-image-information-mining-pbLBNA26548/?CatalogCategoryID=9.EKABstN84AAAEjuJAY4e5L

Abstract

The multitude of sensors used to acquire Earth Observation (EO) images have led to the creation of an extremely various collection of data. Along with appropriate methods able to work with great amount of data, informat ion retrieval process requires algorithms to cope with a range of input imagery. Even if the geometry and the manner of creating Synthetic Aperture Radar (SAR) images are totally different than multispectral data, there are attempts of finding a common ground such that optical image indexing algorithms can be applied for SAR data and vice versa. Moreover, new concepts must be defined in order to obtain satisfying results, enabling measurements and comparisons between the extracted features [4]. Regarding this idea, the goal is to develop an application capable to join feature extraction algorithms and classification algorithms . Its success will sustain the integration of a reliable EO data search engine. This paper presents a framework for feature extraction and classification aiming to support EO image annotation. Weber Local Descriptors (WLD), Gabor filter and Support Vector Machine (SVM) are combined in order to define an application to be tested on both SAR and optical data.

Item URL in elib:https://elib.dlr.de/94218/
Document Type:Conference or Workshop Item (Poster)
Title:A Framework for Benchmarking of Feature Extraction Methods in Earth Observation image Analysis
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Georgescu, Florin-AndreiMilitary Technical Academy, RomaniaUNSPECIFIED
Vaduva, CorinaPolitehnica University of Bucharest, RomaniaUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Răducanu, DanTechnical Academy, RomaniaUNSPECIFIED
Date:2014
Journal or Publication Title:Proceedings of ESA-EUSC-JRC 2014 - 9th Conference on Image Information Mining Conference: The Sentinels Era
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.2788/25852
Page Range:pp. 81-84
Editors:
EditorsEmail
Soille, PierreJoint Research Centre, European Commission, Italy
Marchetti, Pier GiorgioEuropean Space Agency, Italy
Iapaolo, MicheleEuropean Space Agency, Italy
Colaiacomo, LucioEuropean Union Satellite Centre, Spain
Datcu, Mihaimihai.datcu@dlr.de
Publisher:EU
ISSN:1831-9424
ISBN:978-92-79-36160-9
Status:Published
Keywords:high resolution SAR image, data mining, image annotation, statistical local descriptors , SVM, WLD, Gabor filter
Event Title:ESA-EUSC-JRC 2014
Event Location:Bucharest, Romania
Event Type:international Conference
Event Dates:05-07 March 2014
Organizer:ESA/JRC
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 hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By:INVALID USER
Deposited On:07 Jan 2015 15:50
Last Modified:07 Jan 2015 15:50

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