%0 Journal Article
%T Adaptive thresholding for image denoising via sationary Contourlet transform<br>基于平稳Contourlet变换的自适应阈值去噪*
%A CHENG Guang-quan
%A CHENG Li-zhi
%A <br>程光权
%A 成礼智
%J 计算机应用研究
%D 2008
%I 
%X Stationary Contourlet transform with shifl-invariant was applied to image denoising, which could capture the intrinsic geometrical structure of image. Meanwhile, the adaptive Bayes threshold with hard threshold function was implemented to image denoising. The experimental results show that the method can get higher PSNR value and better visual effect compared with other methods.
%K stationary Contourlet transform
%K image denoising
%K shift-invariant
%K BayesShrink<br>平稳Contourlet变换
%K 图像去噪
%K 平移不变性
%K 贝叶斯萎缩
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=4239288FEF6F52F6A7B2091359F0E12E&yid=67289AFF6305E306&vid=C5154311167311FE&iid=0B39A22176CE99FB&sid=8143FF92EEF26F96&eid=FE6B7E9BDCCDBAA6&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=9