%0 Journal Article
%T Anomaly Target Detection in Hyperspectral Imagery Based on Band Subset Fusion by Fuzzy Integral<br>高光谱图像波段子集模糊积分融合异常检测
%A Di Wei
%A Pan Quan
%A Zhao Yong-qiang
%A He Lin
%A <br>邸韡
%A 潘泉
%A 赵永强
%A 贺霖
%J 电子与信息学报
%D 2008
%I 
%X An anomaly target detection method based on the high correlation band subsets and fuzzy integral fusion is presented to deal with detecting unknown target in unknown background for hyperspectral imagery. Original hyperspectral data is divided into several continuous band subsets according to the high correlation within the subset. Applying nonparametric kernel density estimation to the RX detector output of each subset to obtain its probability density function (pdf), and a nonparametric fuzzy membership function is constructed; based on the eigenvalues in spectral dimension, a target signal-noise-ratio is defined to measure the degree of importance of detection result from each subset; finally, decision fusion is implemented through Sugeno fuzzy integral method. Experiments on visible/near-infrared OMIS-I hyperspectral imagery justify the effectiveness of the algorithm.
%K Hyperspectral imagery
%K Anomaly target detection
%K Detection fusion
%K Band subset
%K Fuzzy integral<br>高光谱图像
%K 异常目标检测
%K 检测融合
%K 波段子集
%K 模糊积分
%K 光谱图像
%K 波段子集
%K 模糊积分
%K 决策级融合
%K 异常检测
%K Fuzzy
%K Integral
%K Fusion
%K Band
%K Based
%K Hyperspectral
%K Target
%K Detection
%K 有效性
%K 算法
%K 实验
%K 近红外波段
%K 可见光
%K 使用
%K Sugeno
%K 程度
%K 结果
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=D77F8560DFA86DA0365684067340896A&yid=67289AFF6305E306&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=866F8A6B640835A7&eid=273ADA1BCEFE8C00&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=1&reference_num=15