This paper proposes a de-noising algorithm for SAR images based on Shearlets transform. Shearlets transformation is multi-scale geometric analysis which possesses the advantages of Contourlet transform and Curvelet transform. For a singular curve or surface containing C2 high-dimensional signals, it is an optimal approximation. We apply Shearlets to approach SAR images, and use a bivariate threshold according to the Bayesian estimation theory to perform image de-noising. The obtained results show an increase of 2 dB in PSNR as compared to the Contourlet-based method with a bivariate threshold. Compared with the nonsubsampled Contourlet method with a bivariate threshold, the proposed method gives a higher PSNR and smoother denoised images. In addition, computation complexity is reduced.
LIU Shuai-qi, HU Shao-hai, XIAO Yang
. De-noising of SAR Images Based on Shearlets Transform[J]. Journal of Applied Sciences, 2012
, 30(6)
: 629
-634
.
DOI: 10.3969/j.issn.0255-8297.2012.06.012
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