1 January 2003 Synthetic aperture radar surface reflectivity estimation using a marked point-process speckle model
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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.
© (2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Jihad Salah Daba, Jihad Salah Daba, Mark R. Bell, Mark R. Bell, } "Synthetic aperture radar surface reflectivity estimation using a marked point-process speckle model," Optical Engineering 42(1), (1 January 2003). https://doi.org/10.1117/1.1523052 . Submission:
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