Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images
| Main Authors: | Mario Mastriani, Alberto E. Giraldez |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2008
|
| Online Access: |
https://zenodo.org/record/1330507 |
Daftar Isi:
- 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.