De-noising of SAR Images Based on Shearlets Transform
Xiao Ping Yang · 2012
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.