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3-D terrain from synthetic aperture radar images

Content Provider	IEEE Xplore Digital Library
Author	Bors, A.G. Hancock, E.R. Wilson, R.C.
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci., York Univ., UK (Bors, A.G.)
Abstract	Surface analysis is important for automatic terrain cartography and for airborne navigation. This paper proposes a new approach to shape-from-shading (SFS) in synthetic aperture radar (SAR) images. The SFS problem is embedded in a Bayesian framework. We maximize the surface orientation probability using SAR image statistics, local smoothing and constraints imposed by object discontinuities. We model the statistics of the SAR image distribution as a product between the Rayleigh and Bessel functions. We derive the optimal edge detector for this distribution. The resulting edges are classified as ridges and ravines according to a statistical test. Afterwards, the edges are used as constraints in the estimation of the surface normals. We propose various smoothing algorithms for the vector field of surface normals using robust statistics and surface curvature consistency. The results provided by these algorithms are compared with those given by local averaging.
Starting Page	63
Ending Page	72
File Size	416332
Page Count	10
File Format	PDF
ISBN	0769506402
DOI	10.1109/CVBVS.2000.855251
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Statistical distributions Smoothing methods Navigation Synthetic aperture radar Bayesian methods Probability Detectors Testing Robustness
Content Type	Text
Resource Type	Article

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