Denoising of MRI and X-Ray images using dual tree complex wavelet and Curvelet transforms

The Medical Images normally have a problem of high level components of noises. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. Denoising is used to remove the noise from corrupted image, while retaining the edges and other detailed features as much as possible. In this paper, to find out denoised image the Dual tree complex wavelet and Curvelet transforms based methods are used and we have evaluated and compared performances of Dual tree complex wavelet transform method and the Curvelet transform method based on PSNR (Peak signal to noise ratio) between original image and denoised image. Simulation and experiment results for an image demonstrate that PSNR of the Curvelet transform method is high than Dual tree complex wavelet method. Therefore, the image after denoising has a better visual effect. In this paper, these two methods are implemented on MRI and X-ray images for denoising by using MATLAB.