Title :
Image domain feature extraction from synthetic aperture imagery
Author :
Koets, Michael A. ; Moses, Randolph L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
We consider the problem of estimating a parametric model that describes radar backscattering from synthetic aperture radar imagery. We adopt a scattering center model that incorporates both frequency and aspect dependence of scattering. We develop an approximate maximum likelihood algorithm for parameter estimation directly on regions of the SAR image. The algorithm autonomously selects model order and structure. Results are presented for both synthetic and measured SAR imagery, and algorithm accuracy is compared with the Cramer-Rao bound
Keywords :
backscatter; electromagnetic wave scattering; feature extraction; maximum likelihood estimation; radar clutter; radar imaging; synthetic aperture radar; Cramer-Rao bound; SAR image; SAR imagery; algorithm accuracy; approximate maximum likelihood algorithm; aspect dependence; clutter model; frequency dependence; image domain feature extraction; measured SAR imagery; model order; model structure; parameter estimation; parametric model estimation; radar backscattering; scattering center model; statistical properties; synthetic SAR imagery; synthetic aperture radar imagery; Feature extraction; Frequency domain analysis; Frequency estimation; Optical scattering; Parameter estimation; Parametric statistics; Radar imaging; Radar scattering; Scattering parameters; State estimation;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.758402
