%0 Journal Article
%T Multiscale denoising algorithm based on Shearlet frame<br>基于Shearlet框架的多尺度去噪算法
%A WANG Xiao-ming
%A FENG Xin
%A DANG Jian-wu
%A <br>王晓明
%A 冯　鑫
%A 党建武
%J 计算机应用研究
%D 2012
%I 
%X One of the most common shortcomings of the frameworks of the system Curverlet and Contourlet is lack of providing a unified treatment of the continuum and digital world. Now Shearlet systems are the only systems which satisfy this property, yet still deliver optimally sparse approximations of images. This paper presented a band-limited Shearlet for multi-scale analysis. It used fast PPFT transformation to images, weighted and windowing treatment to get Shearlet coefficient, then optimized the decomposed coefficient of the image noise through the SURE-LET, and finally obtained the denoised image by inverse Shearlet transform. The experimental results show that, compared with the current denoising algorithm, the algorithm takes the certain advantages in the PSNR, SSIM and time.
%K image denoising
%K Shearlet transform
%K sparse representation
%K SURE-LET transform
%K fast PPFT<br>图像去噪
%K Shearlet变换
%K 稀疏表示
%K SURE-LET变换
%K 快速PPFT
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=3178011684088478A08B8750EE0F5171&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=DF92D298D3FF1E6E&sid=D40EDD5739609615&eid=28643B6E97E46912&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12