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Enhancement and analysis in MRI image denoising for different filtering techniques

Abstract The techniques for removal of noise have become an important tool. Image denoising has become an important pre processing part of images. In past, many algorithms for the denoising of images have been proposed. Noise removal is still a challenging task. Noise in an image can occur due to transmission or during capturing or due to external factors. Noises are present in images which lead to the degradation and bad quality of images. Medical images consist of the vital information about the organs and tissues inside the human body and which are used for the diagnosis and treatment of various diseases or for other medical purposes. Medical images needs to be noise free as these medical images consists of important and essential information about a person health which needs to be diagnosed and proper treatment based on this is to be given. The quality of the MRI images is affected by the noises which are present in an image. So, we need to pre-process an image which can be done by the filtering method. The denoising is done for the removal of noise while retaining and also not distorting the quality of the processed and filtered image. The noises which are most commonly present in the medical images are Speckle, Salt and Pepper and Gaussian noise. In this paper, the medical MRI images are taken for the analysis and comparison on gray scale images after converting the images from RGB. The filters which are used for the noise removal are Order Filter, Gabor Filter, Arithmetic Mean Filter. The comparison and analysis is done on the basis of PSNR, MSE and RMSE values which are computed by using MATLAB coding. The experimental evaluation shows the significant removal of noise.