Shearlet-based adaptive MMSE estimator for image denoising
Wei Tian, Hanwen Cao, Chengzhi Deng · 2010
An adaptive Bayesian estimator for image denoising in shearlet domain is presented, where the Bessel K Form (BKF) densities are used as the prior model of shearlet coefficients of images. The BKF densities are shown to fit very well to the observed noise-free histograms. Under this prior, a Bayesian sheartlet estimator is derived by using the minimum mean square error (MMSE) rule. Finally, a simulation is carried out to show the effectiveness of the new estimator. Experimental results show the proposed method can effectively reduce noise and remain edges, obtain better visual effect and higher PSNR.