Comparative Analysis of Noise Reduction Techniques for Brain MRI Image

Abstract

The comparative analysis of noise reduction techniques for brain MRI images delves into the evaluation of various noise types, including salt and pepper, Gaussian, and speckle noise. This study considers three prominent filters: the median filter, non-local means (NLM) algorithm, and Gaussian filter, along with performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Squared Error (MSE), and Entropy. In summary, the NLM filter is robust for speckle and Gaussian noise, excelling quantitatively and visually, while the median filter is preferred for salt and pepper noise when preserving image details is crucial. This analysis provides insights for informed decision-making in enhancing brain MRI image quality.