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Combined Edge Segment Texture Analysis for the Detection of Damaged Buildings in Crisis Areas

Klonus, Sascha and Tomowski, Daniel and Ehlers, Manfred and Reinartz, Peter and Michel, Ulrich (2012) Combined Edge Segment Texture Analysis for the Detection of Damaged Buildings in Crisis Areas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5 (4), pp. 1118-1128. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2012.2205559 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/xpl/

Abstract

This paper describes the results of a new combined method that consists of a cooperative approach of several different algorithms for automated change detection. These methods are based on isotropic frequency filtering, spectral and texture analysis, and segmentation. For the frequency analysis, different band pass filters are applied to identify the relevant frequency information for change detection. After transforming the multitemporal images using a fast Fourier transform and applying the most suitable band pass filter to extract changed structures, we apply an edge detection algorithm in the spatial domain. For the texture analysis, we calculate the parameters energy and homogeneity for the multitemporal datasets. Then a principal component analysis is applied to the new multispectral texture images and subtracted to get the texture change information. This method can be combined with spectral information and prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination of the change algorithms is applied to calculate the probability of change for a particular location. This Combined Edge Segment Texture (CEST) method was tested with high-resolution remote-sensing images of the crisis area in Darfur (Sudan). Our results were compared with several standard algorithms for automated change detection, such as image difference, image ratio, principal component analysis, multivariate alteration detection (MAD) and post classification change detection. CEST showed superior accuracy compared to standard methods.

Item URL in elib:https://elib.dlr.de/76770/
Document Type:Article
Title:Combined Edge Segment Texture Analysis for the Detection of Damaged Buildings in Crisis Areas
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Klonus, SaschaUniversität OsnabrückUNSPECIFIED
Tomowski, DanielUniversität OsnabrückUNSPECIFIED
Ehlers, ManfredUniversität OsnabrückUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.deUNSPECIFIED
Michel, UlrichUniversität HeidelbergUNSPECIFIED
Date:August 2012
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:5
DOI :10.1109/JSTARS.2012.2205559
Page Range:pp. 1118-1128
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Change detection, disaster, edge detection, segmentation
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: Reinartz, Prof. Dr.. Peter
Deposited On:30 Jul 2012 09:13
Last Modified:31 Jul 2019 19:37

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