Title :
Bayesian wavelet shrinkage with edge detection for SAR image despeckling
Author :
Dai, Min ; Peng, Cheng ; Chan, Andrew K. ; Loguinov, Dmitri
Author_Institution :
Electr. Eng. Dept., Texas A&M Univ., College Station, TX, USA
Abstract :
In this paper, we present a wavelet-based despeckling method for synthetic aperture radar images and derive a Bayesian wavelet shrinkage factor to estimate noise-free wavelet coefficients. To preserve edges during despeckling, we apply a modified ratio edge detector to the original image and use the obtained edge information in our despeckling framework. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test images.
Keywords :
Bayes methods; edge detection; geophysical signal processing; geophysical techniques; image denoising; radar imaging; remote sensing by radar; speckle; synthetic aperture radar; wavelet transforms; Bayesian wavelet shrinkage; MMSE estimation; SAR image despeckling; edge detection; edge information; edge preservation; minimum mean square error; noise-free wavelet coefficients; ratio edge detector; stationary wavelet transform; synthetic aperture radar image; wavelet-based despeckling method; Bayesian methods; Detectors; Discrete wavelet transforms; Filters; Image edge detection; Noise reduction; Radar detection; Wavelet coefficients; Wavelet domain; Wavelet transforms; MMSE; Minimum mean square error; SWT; estimation; ratio edge detector; stationary wavelet transform; wavelet shrinkage;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2004.831231
