%0 Conference Paper
%A Nguyen, Thanh Trung
%A Trinh, Dinh Hoan
%A Nguyen, Linh Trung
%B 9th International Conference on Advanced Technologies for Communications (ATC)
%C Hanoi, Vietnam
%D 2016
%F SisLab:2187
%P 293-296
%T An efficient example-based method for CT image denoising based on frequency decomposition and sparse representation
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2187/
%X In this paper we present an effective example-based method for Gaussian denoising of CT images. In the proposed method, an image is considered as a sum of the three frequency bands: low-band, middle-band and high-band. We assume that the noise component is often mixed into the middle-band and the high-band and thus in order to better preserve the high-frequency details in the image we perform denoising on these two bands. The proposed denoising method is based on a sparse representation model in which a set of standard images is used to construct the example dictionaries. The experimental results demonstrate that the proposed method can preserved very good the high-frequency details. The objective and subjective comparisons also show that our method outperforms other state-of-the-art denoising methods.