Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)

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Image Denoising Using Gaussian Scale Mixtures in Lifting Stationary Wavelet Coefficient

Authors
Dongmei Zhang, Minzhi Wang, Jianhua Liu, Zhong Xiao
Corresponding Author
Dongmei Zhang
Available Online September 2012.
DOI
10.2991/emeit.2012.405How to use a DOI?
Keywords
Lifting stationary wavelet transform, GSM, BLS
Abstract

A new method for image denoising is proposed in this paper. Firstly, apply the Lifting Stationary Wavelet transform on the denoised image. Secondly, Gaussian scale mixtures (GSM) is combined with the marginal distributions of neighbor coefficients in the nonsub-sampled contourlet domain are modeled. The Bayes least square estimation is adopted to evaluate high pass coefficient to remove additive white Gaussian noise. Finally, inverse Lifting Stationary Wavelet transform is applied on the denoised coefficients to reconstruction the denoised image.

Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
Series
Advances in Intelligent Systems Research
Publication Date
September 2012
ISBN
10.2991/emeit.2012.405
ISSN
1951-6851
DOI
10.2991/emeit.2012.405How to use a DOI?
Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Dongmei Zhang
AU  - Minzhi Wang
AU  - Jianhua Liu
AU  - Zhong Xiao
PY  - 2012/09
DA  - 2012/09
TI  - Image Denoising Using Gaussian Scale Mixtures in Lifting Stationary Wavelet Coefficient
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 1829
EP  - 1832
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.405
DO  - 10.2991/emeit.2012.405
ID  - Zhang2012/09
ER  -