%0 Journal Article
%T Markov network-based nonlinear algorithm of face image super-resolution<br>基于马尔可夫网络人脸图像超分辨率非线性算法*
%A XIONG Yi
%A HUANG Dong-jun
%A <br>熊异
%A 黄东军
%J 计算机应用研究
%D 2009
%I 
%X This paper researched single face image super resolution algorithms based on learned image examples. It used patch-based Markov network to express the mechanism of super-resolution processing. After dividing the high-resolution images and the corresponding low-resolution ones into patches, set up the training dataset. Considering the requirements of Markov network computing and the difference among the images in training dataset, it proposed a patch position constraint operation for searching the matched patch and a nonlinear searching algorithm. These techniques could decrease the complexity of the searching operation and increase the effect of matching. After collecting the matched high-resolution patches, the proposed method directly used them to integrate an output image. Experimental results demonstrate that the algorithm has a better performance and higher efficiency.
%K face image
%K super resolution
%K Markov network
%K non-linear search<br>人脸图像
%K 超分辨率
%K 马尔可夫网络
%K 非线性搜索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=05A584D5EC69F8B623E7316A2A2B4547&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=5D311CA918CA9A03&sid=F710A9560A1BC251&eid=BEFEF55A1BF6A334&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10