Reduction of Gaussian noise from Computed Tomography Images using Optimized Bilateral Filter by Enhanced Grasshopper Algorithm

Abstract

Medical image de-noising is most important pre-processing task in the field of medical science as medical images plays pivotal role to diagnose any abnormality or disease in the human body. Accurate diagnosis requires noise free medical images and with the presence of noise false decision may be taken by the radiologists or doctors. Many filters have been developed to eliminate noise signals from medical images but there is still a chance to get better results. In this paper Bilateral Filter has been used to de-noise the medical images. However the performance of bilateral filter has been improved using Enhanced Grasshopper optimization Algorithm. This technique optimizes the parameters of Bilateral Filter which gives better results in terms of various performance index parameters.