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Kalman's shrinkage for wavelet-based despeckling of SAR images

2016/07/31 by Mario Mastriani, Mastriani, Mario, Alberto Giráldez +1
Computer Science · Engineering · #Image and Signal Denoising Methods #Image Processing Techniques and Applications #Advanced Image Fusion Techniques

paper · pdf · doi:10.48550/arxiv.1608.00273

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.

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