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Evaluation of Retrieved Categories from a TerraSAR-X Benchmarking Data Set

Dumitru, Corneliu Octavian and Schwarz, Gottfried and Datcu, Mihai (2018) Evaluation of Retrieved Categories from a TerraSAR-X Benchmarking Data Set. IGARSS 2018, 22.-27. Jul. 2018, Valencia, Spain.

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Official URL: https://www.igarss2018.org/default.asp

Abstract

Advanced interpretation of satellite images calls for automated content analysis as well as interactive content search. A typical example of such systems is EOLib, an ESA funded project that already demonstrated the application potential of TerraSAR-X data within a satellite payload ground segment. In this paper, we analyze the validation results of image content classification using a large set of selected TerraSAR-X images. The classification was done with a cascaded learning method. The main advantage of this method is a coarse-to-fine approach for semantically annotating pixel patches with decreasing size. Once a reliable label is found for a given pixel patch, no further subdivision into still smaller patch sizes is necessary. This leads to a considerable reduction of the computational effort during classification of large-size satellite images.

Item URL in elib:https://elib.dlr.de/120527/
Document Type:Conference or Workshop Item (Poster)
Title:Evaluation of Retrieved Categories from a TerraSAR-X Benchmarking Data Set
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Dumitru, Corneliu OctavianCorneliu.Dumitru (at) dlr.deUNSPECIFIED
Schwarz, GottfriedGottfried.Schwarz (at) dlr.deUNSPECIFIED
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Date:July 2018
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-4
Status:Published
Keywords:Cascaded learning, satellite image classification, semantic annotation, TerraSAR-X
Event Title:IGARSS 2018
Event Location:Valencia, Spain
Event Type:international Conference
Event Dates:22.-27. Jul. 2018
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 > EO Data Science
Deposited By: Dumitru, Corneliu Octavian
Deposited On:22 Jun 2018 11:55
Last Modified:30 Nov 2018 12:56

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