%0 Journal Article
	%A Mario Mastriani and  Alberto E. Giraldez
	%D 2008
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 16, 2008
	%T Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images
	%U https://publications.waset.org/pdf/3542
	%V 16
	%X 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.
	%P 1213 - 1219