%0 Journal Article
%T Improved image deblurring based on combination of generalized Gaussian distribution and nonlocal-means<br>改进的广义高斯分布与非局部均值图像去模糊
%A YANG Xin-xin
%A WANG Zhi-ming
%A <br>杨欣欣
%A 王志明
%J 计算机应用研究
%D 2012
%I 
%X In order to improve the traditional algorithm can't reserve the detail information of image defects, and obtain better image to the blurring effect, this paper proposed a new image deblurring algorithm based on generalized Gaussian distribution and NL-means. Firstly, it proposed the blurred image with the wavelet transform, and then estimated scale parameter and shape parameter of generalized Gaussian distribution model with OMLE and classical Newton-Raphson algorithm. It used these two parameters were used to improve initial image weights calculating method which was singly judged by decay rate of exponential function and restricted with only one algorithm. Experimental results on several typical images indicate that the proposed algorithm gives superior effects to initial NL-means and has a good application prospects.
%K image restoration
%K deblurring
%K NL-means algorithm
%K wavelet transform
%K scale parameter
%K shape parameter<br>图像复原
%K 去模糊化
%K 非局部均值算法
%K 小波变换
%K 尺度参数
%K 形状参数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F886A295C1E57CC55E56361BF7F3B48E&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=8D39DA2CB9F38FD0&eid=F53A2717BDB04D52&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10