An Improved MRI Image Denosing Using Global Thresholding Technique

In medical image processing, image denoising plays very vital role in all through the diagnose. Medical images are usually corrupted by random noise in its acquisition and Transmission. Removing noise from the original signal is still a Bottleneck problem for researchers. The main objective of Image denoising techniques is necessary to remove such noises while retaining as much as possible the important signal features. There have been various denoising techniques; each has its own assumptions, advantages, and limitations. In this paper, a new thresholding technique using wavelet has been presented alongwith the standard thresholding techniques like soft and hard thresholding. Magnetic resonance (MR) images are routinely used for medical diagnosis. Denoising of these images to enhance their quality& Clinical parameter for an active area of research. This paper presents the wavelet-based thresholding scheme image denoising and noise suppression in MRI images. The performance of denoising scheme is evaluated in terms of PSNR, MSE and MAE