东南大学学报（英文版）2019，Vol.35Issue(3)：332-340,9.DOI:10.3969/j.issn.1003-7985.2019.03.009
基于小波系数树状结构的组稀疏图像去噪方法
Image denoising method with tree-structured group sparse modeling of wavelet coefficients
摘要
Abstract
In order to enhance the image contrast and quality,inspired by the interesting observation that an increase in noise intensity tends to narrow the dynamic range of the local standard deviation (LSD) of an image,a tree-structured group sparse optimization model in the wavelet domain is proposed for image denoising.The compressed dynamic range of LSD caused by noise leads to a contrast reduction in the image,as well as the degradation of image quality.To equalize the LSD distribution,sparsity on the LSD matrix is enforced by employing a mixed norm as a regularizer in the image denoising model.This mixed norm introduces a coupling between wavelet coefficients and provides a tree-structured group scheme.The alternating direction method of multipliers (ADMM) and the fast iterative shrinkage-thresholding algorithm (FISTA) are applied to solve the group sparse model based on different cases.Several experiments are conducted to verify the effectiveness of the proposed model.The experimental results indicate that the proposed group sparse model can efficiently equalize the LSD distribution and therefore can improve the image contrast and quality.关键词
局部均方差/组稀疏/图像去噪/混合范数/纹理Key words
local standard deviation/group sparse/image denoising/mixed norm/texture分类
信息技术与安全科学引用本文复制引用
张涛,魏海广,莫绪涛..基于小波系数树状结构的组稀疏图像去噪方法[J].东南大学学报（英文版）,2019,35(3):332-340,9.基金项目
The National Natural Science Foundation of China(No.61701004,11504003),the Natural Science Foundation of Anhui Province (No.1708085QA15). （No.61701004,11504003）
