@article{(Open Science Index):https://publications.waset.org/pdf/3542,
	  title     = {Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images},
	  author    = {Mario Mastriani and  Alberto E. Giraldez},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {4},
	  year      = {2008},
	  pages     = {1213 - 1219},
	  ee        = {https://publications.waset.org/pdf/3542},
	  url   	= {https://publications.waset.org/vol/16},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 16, 2008},