This work proposes two methods for MRI denoising that exploit both the sparseness and self-similarity properties of the image. The proposed methods are based on 1) an overcomplete non-local patch grouping PCA hard thresholding and 2) a rotationally invariant nonlocal means filter that uses the output of first filter as a guide image to filter the image.