%0 Journal Article
%T Anomaly Detection in Hyperspectral Imagery Based on Feature Fusion of Band Subsets<br>基于波段子集特征融合的高光谱图像异常检测
%A He Lin
%A Pan Quan
%A Zhao Yongqiang
%A Zhen Jiwei
%A Wei Kun
%A <br>贺霖
%A 潘泉
%A 赵永强
%A 郑纪伟
%A 魏坤
%J 光子学报
%D 2005
%I 
%X Detecting camouflaged targets in an unknown environment presents a great challenge in hyperspectral image analysis since the prior knowledge about targets and background is not available. A nomaly detection method for hyperspectral imagery was proposed for this problem. Features were extracted from subband sets of hyperspectral imagery,then fusion algorithm for detection was implemented by D-S evidence reasoning while basic belief assignment function was constructed involving high-order moments of features. Theoretical analysis and results of experiment verify the effectiveness of the algorithm.
%K Hyperspectral imagery processing
%K Target detection
%K Feature
%K usion
%K Evidence reasoning
%K Band subsets<br>高光谱图像处理
%K 目标检测
%K 特征融合
%K 证据推理
%K 波段子集
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=9F6139E34DAA109F9C104697BF49FC39&aid=85254AA54A2F4BDE&yid=2DD7160C83D0ACED&vid=339D79302DF62549&iid=708DD6B15D2464E8&sid=3E25A065A8F8B129&eid=290C357E8EC0A94B&journal_id=1004-4213&journal_name=光子学报&referenced_num=15&reference_num=18