DocumentCode :
1507039
Title :
Fuzzy fusion techniques for linear features detection in multitemporal SAR images
Author :
Chanussot, Jocelyn ; Mauris, Gilles ; Lambert, Patrick
Author_Institution :
Lab. d´´Autom. et de MicroInf. Ind., Savoie Univ., Annecy, France
Volume :
37
Issue :
3
fYear :
1999
fDate :
5/1/1999 12:00:00 AM
Firstpage :
1292
Lastpage :
1305
Abstract :
This paper is concerned with the automatic detection of linear features in SAR satellite data, with application to road network extraction. After a directional prefiltering step, a morphological line detector is presented. To improve the detection performances, the results obtained on multitemporal data are fused. Different fusion strategies involving different fusion operators are then presented. Since extensions of classical set union and intersection do not lead to satisfactory results (the corresponding operators are either too indulgent or too severe), the first strategy consists of fusing the data using a compromise operator. The second strategy consists of fusing the results computed with two operators that have opposite properties, in order to obtain a final intermediate result. Thanks to the wide range of properties they provide, fuzzy operators are used to test and compare these two fusion strategies on real ERS-1 multitemporal data
Keywords :
feature extraction; geophysical signal processing; geophysical techniques; image sequences; radar imaging; remote sensing by radar; sensor fusion; spaceborne radar; synthetic aperture radar; terrain mapping; SAR; automatic detection; data fusion; feature extraction; fuzzy fusion; geophysical measurement technique; image fusion; land surface; land use; linear feature; linear feature detection; multitemporal SAR image; radar imaging; radar remote sensing; road network; sensor fusion; spaceborne radar; synthetic aperture radar; terrain mapping; Computer vision; Detectors; Feature extraction; Filtering; Nonlinear filters; Radar detection; Radar imaging; Roads; Satellites; Spaceborne radar;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.763290
Filename :
763290
Link To Document :
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