Medical Image Denoising Using a Nonlinear Thresholding Function in Nonsubsampled Contourlet Transform

This paper proposes a new method of medical image denoising based on a new nonlinear thresholding function in Nonsubsampled Contourlet Transform (NSCT) domain. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. The contourlet transform is a new extension of the wavelet transform that provides a multi-resolution and multidirection analysis for two dimension images. The NSCT expansion is composed of basis images oriented at various directions in multiple scales, with flexible aspect ratios. Each coefficient of the NSCT transform is tuned by a polynomial function for denoising. We compared the results of the proposed method with other methods of image de-noising. Experimental results show that the proposed approach can obtain better visual results and higher PSNR values.