%0 Journal Article
%T MULTICATEGORY TARGETS DETECTION OF HYPERSPECTRAL IMAGERY BASED ON ADAPTIVE STRUCTURED BACKGROUND AND SHAPE-FEATURE SUBSPACE<br>自适应结构化背景和形状特征子空间高光谱图像多类目标检测
%A HE Lin
%A PAN Quan
%A DI Wei
%A <br>贺霖
%A 潘泉
%A 邸韡
%J 红外与毫米波学报
%D 2007
%I Science Press
%X A new detection algorithm was presented to detect multicategory targets of known shape-feature and unknown spectral signature in unknown environment. Firstly, a point spread function was constructed via high-order moments of quadratic form of data samples to obtain adaptive structured background. Then, a priori shape-features of targets were utilized to construct a shape-feature subspace which is matched with high-dimension spectral signature space. Theoretic analysis and the results of experiment verify the effectiveness of the algorithm.
%K information processing technology
%K hyperspectral imagery
%K multicategory targets detection
%K shape-feature subspace
%K structured background<br>信息处理技术
%K 高光谱图像
%K 多类目标检测
%K 形状特征子空间
%K 结构化背景
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=7DA3378AF5C9F5A6&yid=A732AF04DDA03BB3&vid=96C778EE049EE47D&iid=94C357A881DFC066&sid=A5111BA190517959&eid=EF78DD85C21CB57F&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=0&reference_num=12