%0 Journal Article
%T Reconstruction of Superresolution Image Using Generalized Gaussian Markov Random Fields Model<br>基于通用高斯马尔可夫随机场模型的图像超分辨率重建
%A HUANG Hua
%A LI Jun
%A QI Chun
%A ZHU Shi-Hua
%A <br>黄华
%A 李俊
%A 齐春
%A 朱世华
%J 计算机科学
%D 2005
%I 
%X An image super-resolution reconstruction method based on generalized Gauss-Markov random fields (GGM- RF)model is presented in this paper. The process of searching solution and experimental results are presented and ana- lyzed. Compared with Compound Markov and Huber-Markov random models, GGMRF model has the merits of easier solving and reduced computational expense, because it does not need to discriminate edge or line process. The experi- mental results show that for the case of lightly noised image, this method has a better visual effect on the reconstructed image.
%K Superresolution
%K Image reconstruction
%K GGMRF<br>超分辨率
%K 图像重建
%K GGMRF模型
%K 马尔可夫随机场
%K 随机场模型
%K 图像超分辨率
%K 高斯
%K 通用
%K Markov
%K MRF模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=05C2BEB411C21A8C&yid=2DD7160C83D0ACED&vid=9971A5E270697F23&iid=708DD6B15D2464E8&sid=64963996248CBF47&eid=2BA123C6EB9D54C2&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=11