DocumentCode :
3690920
Title :
Road damage detection from VHR remote sensing images based on multiscale texture analysis and dempster shafer theory
Author :
Moslem Ouled Sghaier;Richard Lepage
Author_Institution :
É
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
4224
Lastpage :
4227
Abstract :
Infrastructures damage detection in case of major disasters is one of the most discussed problems and represent an active field of research in remotely sensed imaging. In this paper, a novel method designed for fast roads damage extraction is proposed since these structures are important in the delivery of assistance and to manage the intervention of the emergency teams on ground. The proposed methodology includes first an already completed step that consists in extracting the road network from both the pre- and post-disaster images. Then, a multiscale segmentation based on the wavelet transform is performed on the road surface and the obtained objects from the two coregistered images are compared. Finally, the Dempster Shafer theory is applied to decide the membership class of each object in a first step, and then identify the nature of changes using the multidimensional evidential reasoning. Images acquired by the Geo-Eye satellite before and after the earthquake that hits Port-au-Prince (Haiti) on January 2010 are used in the experiments.
Keywords :
"Roads","Image segmentation","Remote sensing","Satellites","Earthquakes","Image resolution","Image edge detection"
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
ISSN :
2153-6996
Electronic_ISBN :
2153-7003
Type :
conf
DOI :
10.1109/IGARSS.2015.7326758
Filename :
7326758
Link To Document :
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