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|Title:||Synthetic aperture radar surface reflectivity estimation using a marked point-process speckle model||Authors:||Daba, Jihad S.
Bell, Mark R
|Affiliations:||Department of Electrical Engineering||Issue Date:||2003||Part of:||The journal of optical engineering||Volume:||42||Issue:||12||Start page:||478||End page:||481||Abstract:||
This paper presents stochastic models and estimation algorithms for speckled images, with an emphasis on synthetic-aperture-radar images, and where the speckle may not be fully developed. We treat speckle from a novel point of view: as a carrier of useful surface information rather than as contaminating noise. The stochastic models for surface scattering are based on a doubly stochastic marked Poisson point process. For each of these surface-scattering statistical models, we present estimation algorithms to determine the average surface reflectivity and scatterer density within a resolution cell, using intensity measurements of speckled images. We show that the maximum-likelihood estimator is optimal in the sense that the variance of the error is the smallest possible using any conceivable estimate having the same bias with the same data.
|Appears in Collections:||Department of Electrical Engineering|
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