NDLI: Supervised fuzzy classification of SAR data using multiple sources

Content Provider	IEEE Xplore Digital Library
Author	Jaeger, G. Benz, U.C.
Copyright Year	1999
Description	Author affiliation: Inst. of Radio Frequency Technol., German Aerosp. Res. Establ., Wessling, Germany (Jaeger, G.)
Abstract	Synthetic aperture radar images contain a lot of information, but they are difficult to interpret. It is important to extract information dependent on the application to increase the acceptance of radar data. A supervised learning system is necessary to implement the required adaptability. The authors' fuzzy approach allows one to cope with uncertainties due to linguistic class definition, vague models, mixed pixels and noisy input data. In some cases single-channel classification already leads to satisfying results, however it is often desirable if not necessary to take more than one source of information into account. They show in this paper how the information contained in multiple channels, e.g. the four channels of a full polarimetric SAR and/or information from different sources, can be combined automatically to obtain a final classification with high accuracy. To cope with the problem of different reliability of the available channels as well as in their classification technique the authors make extensively use of fuzzy logic. The proposed methods are computational efficient and increase the accuracy of the classification compared to single channel methods. The performance of these techniques is demonstrated on ESAR data.
Starting Page	1603
Ending Page	1605
File Size	338253
Page Count	3
File Format	PDF
ISBN	0780352076
DOI	10.1109/IGARSS.1999.772033
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-28
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Supervised learning Uncertainty Fuzzy systems Histograms Radio frequency Synthetic aperture radar Data mining Radar applications Radar imaging Information resources
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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