(untitled) (International Journal of Engineering and Computer Science, 2015)
In medical image processing, medical images are corrupted by different type of noises. It is very important to obtain precise images to facilitate accurate observations for the given application. Removing of noise from medical images is now a very challenging issue in the field of medical image processing. Most well known noise reduction methods, which are usually based on the local statistics of a medical image, are not efficient for medical image noise reduction. This paper presents a new and fast method for removal of noise and blur from Magnetic Resonance Imaging (MRI) using wavelet transform. In this work we utilize a fact that wavelets can represent magnetic resonance images well, with relatively few coefficients. We use this property to improve MRI restoration with arbitrary k-space trajectories. Image restoration is posed as an optimization problem that also could be solved with the Fast iterative shrinkage thresholding algorithm (FISTA)Using mathematical analysis we show that our non linear method is performing fast than other regularization algorithms.