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.
Feature detection in synthetic aperture radar images using fractal error
1997 IEEE Aerospace Conference ; 1 ; 187-195 vol.1
1997-01-01
987168 byte
Conference paper
Electronic Resource
English
Feature Detection in Synthetic Aperture Radar Images Using Fractal Error
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