Improving Estimation in Speckled Imagery
نویسندگان
چکیده
We propose an analytical bias correction for the maximum likelihood estimators of the G0 I distribution. This distribution is a very powerful tool for speckled imagery analysis, since it is capable of describing a wide range of target roughness. We compare the performance of the corrected estimators with the corresponding original version using Monte Carlo simulation. This second-order bias correction leads to estimators which are better from both the bias and mean square error criteria.
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