Impulse noise reduction in medical images with the use of switch mode fuzzy adaptive median filter

Abstract

In this paper, a novel fuzzy adaptive median filter is presented for the noise reduction in MR images corrupted with heavy impulse (salt&pepper) noise. We propose a switch mode fuzzy adaptive median filter (SMFAMF) for removing highly corrupted salt&pepper noise without destroying edges and details in the image. The SMFAMF filter is an improved version of adaptive median filter (AMF) in order to reduce additive impulse noise in the images. The proposed filter can preserve details in the images better than AMF while suppressing additive salt&pepper or impulse type noises. In this paper, we placed our preference on bell-shaped membership function with adaptive parameters instead of triangular membership function without variable coefficients in order to observe better results. Experiments with the magnetic resonance (MR) image from healthy subject, an MR image having the opaque material, and an MR image having disease demonstrate the mean square error (MSE), root mean square error (RMSE), signal-to-noise ratio (SNR), and peak signal-to-noise ratio (PSNR) of the proposed method. The results show that the proposed method can be useful for MR images with impulse type noises.