Quadrilateral Scaled Threshold Weighted Averaging Filter for MRI Denoising

Image denoising of Magnetic Resonance Imaging (MRI) by manifold approach focuses on the removal of inhomogeneous Gaussian and Rician noise without blurring the fine anatomical structures. Non Local Means (NLM) filter, the popular denoising technique, does not hold well for edge preservation of images with low Signal to Noise Ratio (SNR). Hence, an alternative formulation of NLM filter is required. This paper presents a quadrilateral scaling method based on image gradients for change in the isotropic nature of NLM and provides an estimate for edge orientation. A new definition of NLM weights based on similarity intensity measures that reflect on the noise statistics is introduced. The efficacy and feasibility of the proposed method is demonstrated through simulation. The probable reduction in time consumption is illustrated.