A novel implementation for brain MRI noise reduction

Abstract

In this paper proposed algorithm is based on Dual Tree-CWT and Nonlocal Mean filtering processes is used to eliminate Rician noise from the brain magnetic resonance images. The noise reduction is done using two stage processes, first sparse DT-CWT is applied, which allows for distinction of data directionality in the transform space and then Rotational invariant version of Non-Local Mean filter is applied. The proposed algorithm is tested with different Rician noise levels of brain MR Images. Even the Image is degraded by 15% Rician noise the PSNR and SSIM obtained are 23dB and 0.93 which is a better performance as compared to Anisotropic Diffusion Filter (ADF), Non local Maximum Likelihood (NLML), Nutrosophic Set Median Filter (NS median).