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An efficient example-based method for CT image denoising based on frequency decomposition and sparse representation

Thanh Trung Nguyen and Dinh Hoan Trinh and Linh Trung Nguyen (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.

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Official URL: http://dx.doi.org/10.1109/ATC.2016.7764792

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.

Item Type:Conference or Workshop Item (Lecture)
Subjects:Electronics and Communications
Divisions:Faculty of Electronics and Telecommunications (FET)
ID Code:2187
Deposited By: A/Prof. Linh Trung Nguyen
Deposited On:25 Dec 2016 16:55
Last Modified:25 Dec 2016 16:55

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