Shearlet-Based Adaptive Shrinkage Threshold for Image Denoising

Abstract

An adaptive shrinkage threshold for image denoising in shearlet domain is presented. The shearlet transform not only provides the mean to detect orientations and to lead to sparse representations, but is moreover equipped with a rich mathematical structure similar to wavelets. Finally, a simulation is carried out to show the effectiveness of the new estimator. Experimental results show that the new estimator achieves state-of-art performance in terms of peak signal-to-noise ratio (PSNR) and visual quality.