NDLI: Feature detection in synthetic aperture radar images using fractal error

Content Provider	IEEE Xplore Digital Library
Author	Jansing, E.D. Chenoweth, D.L. Knecht, J.
Copyright Year	1997
Description	Author affiliation: Dept. of Electr. Eng., Louisville Univ., KY, USA (Jansing, E.D.)
Abstract	This paper discusses a technique that will enhance man-made features in SAR images. The technique uses a metric called fractal error. Developed by Cooper, et al. (1994) for aiding photointerpreters in detecting man-made features in aerial reconnaissance images, this metric is based upon the observed propensity of natural image features to fit a fractional Brownian motion (fBm) model. Natural scene features fit this model well, producing a small fractal error. Man-made features, on the other hand, usually do not fit the fBm model well and produce a relatively large fractal error. Therefore the fractal error is useful as a discriminant function for detecting man-made features in SAR imagery. The fractal error metric is defined, an approach to segmentating man-made objects in SAR images is discussed, and the results are presented.
Starting Page	187
Ending Page	195
File Size	987168
Page Count	9
File Format	PDF
ISBN	0780337417
DOI	10.1109/AERO.1997.574413
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-02-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Radar detection Synthetic aperture radar Fractals Image segmentation Reconnaissance Frequency Radar imaging Motion detection Brownian motion
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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