%0 Journal Article
%T An IR Target Detection Algorithm Based on Mixture Probabilistic Kernel Principal Component Jointed with Quadratic Correlation Filter<br>基于混合概率核主成分二次相关红外目标检测
%A WEI Kun
%A ZHAO Yong-qiang
%A GAO Shi-bo
%A PAN Quan
%A ZHANG Hong-cai
%A <br>魏坤
%A 赵永强
%A 高仕博
%A 潘泉
%A 张洪才
%J 光子学报
%D 2008
%I 
%X Based on the feature extraction of principal component,a novel infrared target detection algorithm was proposed which using subspace quadratic synthetic discriminant function (SSQSDF).Firstly,the kernel principal component analysis was extended to mixture probabilistic model,and the latter get the principal component vectors of target samples.Then,training samples and samples to be detected were projected on principal component vectors obtained previously to acquire their low-dimension feature components,and the obtained components are used as the sample parameters for the SSQSDF.The detected samples which had a higher SSQSDF filtering output than given threshold were considered as the detected targets.The proposed algorithm can evidently restrain clutter noise,improve target detection precision.Experimental results under complex scenery demonstrate that the proposed algorithm is feasibility and effectiveness.
%K IR target detection
%K Quadratic correlation filter
%K Kernel principal component
%K Mixture probabilistic model
%K Quadratic synthetic discriminant function<br>红外目标检测
%K 二次相关滤波
%K 核主成分分析
%K 混合概率模型
%K 二次综合判别函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=9F6139E34DAA109F9C104697BF49FC39&aid=0FF15E9D2FEB4C084D536CD3940BB05C&yid=67289AFF6305E306&vid=42425781F0B1C26E&iid=9CF7A0430CBB2DFD&sid=C67DF474DF6F21E1&eid=41092F8E82939C3E&journal_id=1004-4213&journal_name=光子学报&referenced_num=1&reference_num=17