In this paper, we propose an improved method for the removal of additive Gussian white noise from PET-CT images. Different from the traditional sparse representation based denoising methods, our method is composed of two distinctively steps such as the preliminary denoise and the detail compensation. By constructing a sparse representation model, denoising is formulated as an optimization problem that can be solved on an over-complete dictionary. The proposed method effectively trains this dictionary by using K-SVD algorithm with atom replace model. Then the preliminary denoised image is recon...
