@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}, }