DocumentCode :
2933924
Title :
Improving road detection on SAR images using fuzzy fusion methods
Author :
Chanussot, Jocelyn ; Mauris, Gilles ; Lambert, Patrick
Author_Institution :
Savoie Univ., Annecy, France
Volume :
3
fYear :
1999
fDate :
1999
Firstpage :
1807
Abstract :
This paper focuses on the use of fuzzy fusion techniques to improve the automatic detection of linear features on multi-temporal SAR images. Different fusion strategies involving different fusion operators are presented. Since T-norms and T-conorms do not lead to satisfactory results (these operators are respectively too severe and too indulgent), the first strategy consists in fusing the data using a compromise operator. The second strategy consists in fusing the results computed with two operators with opposite properties, in order to obtain a global intermediate result. Thanks to the wide range of behaviours they provide, fuzzy operators are used to test and compare these two fusion strategies on real ERS-1 data
Keywords :
cartography; edge detection; feature extraction; fuzzy set theory; radar imaging; remote sensing by radar; sensor fusion; terrain mapping; SAR images; automatic detection; compromise operator; data fusion; feature detection; fuzzy fusion methods; fuzzy operators; global intermediate result; line detection; linear features; mean operator; multi-temporal images; operators with opposite properties; order weighted averaging operator; real ERS-1 data; road detection; Computer vision; Data mining; Intersymbol interference; Layout; Radar detection; Radar imaging; Roads; Satellites; Synthetic aperture radar; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1999. IMTC/99. Proceedings of the 16th IEEE
Conference_Location :
Venice
ISSN :
1091-5281
Print_ISBN :
0-7803-5276-9
Type :
conf
DOI :
10.1109/IMTC.1999.776132
Filename :
776132
Link To Document :
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