%0 Journal Article
%T Infrared small target detection based on image sparse representation<br>基于图像稀疏表示的红外小目标检测算法
%A ZHAO Jia-Ji
%A TANG Zheng-Yuan
%A YANG Jie
%A LIU Er-Qi
%A ZHOU Yue
%A <br>赵佳佳
%A 唐峥远
%A 杨杰
%A 刘尔琦
%A 周越
%J 红外与毫米波学报
%D 2011
%I Science Press
%X The sparse representation based on over-complete dictionary is a new image representation theory. The redundancy of over-complete dictionary can enable it effectively to capture the geometrical characteristics of the images. In this paper, a novel detection method based on image sparse representation is introduced. The over-complete target dictionary is first constructed with atoms which are produced by two-dimensional Gaussian model. Then the sub-image blocks of the test image are extracted successively and the corresponding coefficients are calculated with the constructed over-complete target dictionary. There is a significant difference between the coefficients of objective and background. Whether the sub-image block contains small target or not can be determined by the index of sparse concentration. Experimental results demonstrate the effectiveness of the proposed method.
%K image sparse representation
%K infrared small target
%K object detection<br>图像稀疏表示
%K 红外小目标
%K 目标检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=BFBBDCB3C31448D37B63BF3F90529E90&yid=9377ED8094509821&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=3F0AF5EDBC960DB0&eid=F1177A9DF1349B63&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=1&reference_num=0