eprintid: 2187
rev_number: 11
eprint_status: archive
userid: 17
dir: disk0/00/00/21/87
datestamp: 2016-12-25 16:55:18
lastmod: 2016-12-25 16:55:18
status_changed: 2016-12-25 16:55:18
type: conference_item
metadata_visibility: show
creators_name: Nguyen, Thanh Trung
creators_name: Trinh, Dinh Hoan
creators_name: Nguyen, Linh Trung
creators_id: trungntktmt@gmail.com
creators_id: hoantd@gmail.com
creators_id: linhtrung@vnu.edu.vn
title: An efficient example-based method for CT image denoising based on frequency decomposition and sparse representation
ispublished: pub
subjects: ECE
divisions: fac_fet
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.
date: 2016
date_type: published
official_url: http://dx.doi.org/10.1109/ATC.2016.7764792
full_text_status: public
pres_type: lecture
place_of_pub: Hanoi, Vietnam
pagerange: 293-296
event_title: 9th International Conference on Advanced Technologies for Communications (ATC)
event_location: Hanoi, Vietnam
event_dates: 12-14 October
event_type: conference
refereed: TRUE
citation:   Nguyen, Thanh Trung and Trinh, Dinh Hoan and Nguyen, Linh Trung  (2016) An efficient example-based method for CT image denoising based on frequency decomposition and sparse representation.  In: 9th International Conference on Advanced Technologies for Communications (ATC), 12-14 October, Hanoi, Vietnam.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2187/1/1570294364.pdf