%0 Journal Article
%T Image Super Resolution Based on Wavelet-domain Local Gaussian Model<br>基于小波域局部高斯模型的图像超分辨率
%A WANG Xue-lin
%A WEN Wei
%A PENG Si-long
%A <br>汪雪林
%A 文伟
%A 彭思龙
%J 中国图象图形学报
%D 2004
%I 
%X An image super-resolution algorithm based on wavelet-domain local gaussian model is proposed. Wavelet-domain local gaussian model approximates the local probability distribution of the wavelet coefficients with a single gaussian function. Because the model adaptively characterizes the local statistics of real-world images, the algorithm presented in this paper specifies the prior distribution of the real-world image through it and converts the image super-resolution problem to a constrained optimization one which can be solved with the conjugate gradient method. Experimental results show that the algorithm properly retrieves various kinds of edges and the PNSR and subjective visual effect of the reconstructed images are improved significantly.
%K image superresolution
%K wavelets
%K local gaussian model
%K conjugate gradient method<br>图像超分辨率
%K 小波变换
%K 局部高斯模型
%K 共轭梯度法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=EB3185DF9EE910BE&yid=D0E58B75BFD8E51C&vid=9CF7A0430CBB2DFD&iid=5D311CA918CA9A03&sid=27A5865B8C0B85C3&eid=7C8C2BAFC9BA0571&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=15