Paper Title
Medical Image Denoising Using Three Dimensional Discrete Wavelet Transform And Bilateral Filter

Medical imaging is one of the most important sub-fileds in the world of science and technology. There is no compromise in the quality of medical images as it is used to diagnose a variety of illness. Developing a significant denoising method plays a major role in image processing. In this paper, image is first decomposed into eight subbands using 3D DWT and bilateral filter and Thresholding methods are incorporated. The approximation coefficient obtained from DWT is filtered using Bilteral filter and the detail coefficients are subjected to Wavelet Thresholding. Hard thresholding and Soft threshold are the commonly used thresholding techniques. For better results, Bayes shrink, Visushrink etc were used to estimate the threshold value. Image is reconstructed by the inverse wavelet transform of the resultant coefficients and then it is filtered using Bilateral filter. MRI images and Ultrasound images are taken as datasets for quantitative validation. The Peak Signal to Noise Ratio (PSNR), Root mean square error (RMSE), Structural Similarity Index (SSIM) are employed to quantify the performance of denoising. Index Terms— Image Denoising, Multi Resolution Analysis, 3d Discrete Wavelet Transform, Bilateral Filter,Wavelet Thresholding