A Novel Statistical High Density Salt-and-Pepper Noise Removal Algorithm for Brain Magnetic Resonance Images.

Brain Magnetic Resonance Imaging (MRI) is a non-invasive technique that produces high quality images of the brain and is most suitable for analysis and diagnosis. However, these images can be soiled with noise during image acquisition or transmission. The paper is targeted at removing high density salt and pepper noise from such medical images using a denoising technique based on centroidal mean formulation. The presented method is tested on various noisy brain MRI images and the obtained results are promising even for images with high density corruptions, which is suggestive of the resiliency of the algorithm.