@inproceedings{SisLab2187,
       booktitle = {9th International Conference on Advanced Technologies for Communications (ATC)},
           title = {An efficient example-based method for CT image denoising based on frequency decomposition and sparse representation},
          author = {Thanh Trung Nguyen and Dinh Hoan Trinh and Linh Trung Nguyen},
         address = {Hanoi, Vietnam},
            year = {2016},
           pages = {293--296},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2187/},
        abstract = {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.}
}