Speckle reduction in SAR images via Shearlet transform-based thresholding

The quality of synthetic aperture radar (SAR) images generally suffers from speckle noise, which damages the radiometric resolution of SAR images. A new speckle reduction method is proposed by thresholding the speckled SAR image coefficients in the Shearlet transform domain. As a powerful multiscale image representation tool, Shearlet tranform enables better preservation of significant detail information in despeckled results. Compared with the wavelet transform, Shearlet transform is more suitable for image restoration applications where detail preservation is highly demanding. Experimental results on real X-band amplitude and intensity SAR images demonstrate the efficacy of the proposed method. A quantitative analysis is also given to show the superiority of the Shearlet-based thresholding method over the translation-invariant wavelet-based counterpart.