%0 Journal Article
%T Image super-resolution with adaptive regularization sparse representation<br>基于稀疏表示的自适应图像超分辨率重建算法
%A ZHANG Yao
%A XU Bin
%A ZHOU Shang-bo
%A ZHENG Jian
%A <br>张　垚
%A 徐　斌
%A 周尚波
%A 郑　坚
%J 计算机应用研究
%D 2013
%I 
%X Conduct research on the existence and uniqueness of sparse resolution in super-resolution image reconstruction and the relationship of edge feature and smoothing noise of super-resolution image. In order to solve these problems, this paper proposed the mean of adaptive regularization. Combining with joint over-complete dictionary, it realized dynamically adjust the regularization parameter. Through super-resolution image reconstruction experiment, it demonstrates that this algorithm is working efficiently and balances edge features and smoothing noise well, which has high PSNR compared with the traditional algorithm.
%K super-resolution
%K adaptive regularization
%K joint dictionary<br>超分辨率
%K 自适应正则化
%K 联合字典
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=523711B464E4FFDF27F079A4CC464D39&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=502AE9EE93CAADD7&eid=27A5865B8C0B85C3&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13