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Journal of Applied Remote Sensing

Novel mixture model for synthetic aperture radar imagery
Author(s): Qiangqiang Peng; Long Zhao
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Paper Abstract

We propose a novel mixture model that combines two special cases of heavy-tailed Rayleigh distribution. These two special families possess the only analytical forms of heavy-tailed Rayleigh distribution. As a consequence, the mixture model has an analytical form. Because heavy-tailed Rayleigh distribution is a member of spherically invariant random process, one can obtain the parameter estimation by the method-of-moments technique. Finally, the mixture model has been tested on various synthetic aperture radar images, and the performance of this model is strong compared with other models such as K distribution, G0 distribution, and heavy-tailed Rayleigh models.

Paper Details

Date Published: 13 December 2012
PDF: 17 pages
J. Appl. Rem. Sens. 6(1) 063616 doi: 10.1117/1.JRS.6.063616
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Qiangqiang Peng, BeiHang Univ. (China)
Long Zhao, BeiHang Univ. (China)

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