  In this paper, a new probability density function (pdf) is proposed to model
the statistics of wavelet coefficients, and a simple Kalman's filter is derived
from the new pdf using Bayesian estimation theory. Specifically, we decompose
the speckled image into wavelet subbands, we apply the Kalman's filter to the
high subbands, and reconstruct a despeckled image from the modified detail
coefficients. Experimental results demonstrate that our method compares
favorably to several other despeckling methods on test synthetic aperture radar
(SAR) images.
