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/).
Cite this article
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 -