电子科技大学学报2017，Vol.46Issue(3)：511-515,5.DOI:10.3969/j.issn.1001-0548.2017.03.006
基于Shearlet变换的泊松噪声图像复原问题研究
Research on Poisson Noise Image Restoration Problems Based on Shearlet Transform
摘要
Abstract
Restoring Poisson noise images has been drawn a lot of attention in recent years.To solve this problem,several regularization methods have been put forward.One of the most famous methods is the Total variation (TV) model.However,the TV model will cause staircasing effects.The total generalized variation (TGV) is the extension of TV.Using TGV as a regularization term to recover the Poission image can eliminate staircase effects but the edge details will not preserved very well.In order to overcome this drawback,based on TGV and Shearlet transform,we propose a new regularization method.The proposed model is solved by the alternating direction method of multiplier (ADMM).The numerical results reflect the efficiency of the new model in dealing with Poisson noise image.关键词
交替方向乘子法/泊松噪声/Shearlet变换/阶梯效应/总广义变差Key words
alternating direction method of multiplier (ADMM)/Poisson noise/Shearlet transform/staircase/total generalized variation分类
信息技术与安全科学引用本文复制引用
李红,王俊艳,李厚彪..基于Shearlet变换的泊松噪声图像复原问题研究[J].电子科技大学学报,2017,46(3):511-515,5.基金项目
国家自然科学基金(51175443,11101071) （51175443,11101071）
四川省科技支撑计划(2015GZX0002) （2015GZX0002）
中央高校基本科研业务费专项资金(ZYGX2016J131,ZYGX2016J138) （ZYGX2016J131,ZYGX2016J138）
