Assessment of non-linear filters for MRI images
Leena Chandrashekar, A. Sreedevi · 2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT) · 2017
Noise is major concern in MRI images. There is always a demand for noise free and enhanced MRI images for accurate diagnosis of brain diseases. Thermal noise, Gaussian noise and Rician noise are some of the noises present in MRI images. The causes for these noises are patient condition, imaging system and unskilled manpower. This leads to poor quality of image, blurring, distortion and difficulty in detection and diagnosis of brain disease. Denoising is a process of removing the noise. The aim of this work is to understand the noise models and non-linear denoising techniques. Anisotropic Filter, Bilateral Filter and Non Local means filter are the non-linear filters used for denoising of MRI images. The performance of the filters is evaluated in terms of PSNR, Entropy, MSE, SSIM and average execution time. The Non-local Means filters gives better PSNR, MSE and SSI for Gaussian denoised MRI images.