[1]赵春晖,王楠楠.基于背景抑制及顶点成分分析的[J].应用科技,2009,36(09):11-14.[doi:oi:10.3969/j.issn.1009-671X.2009.09.003]
 ZHAO Chun hui,WANG Nan nan.Anomaly detection of hyperspectral imagery based on background restrain and VCA[J].Applied science and technology,2009,36(09):11-14.[doi:oi:10.3969/j.issn.1009-671X.2009.09.003]
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基于背景抑制及顶点成分分析的
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《应用科技》[ISSN:1009-671X/CN:23-1191/U]

卷:
第36卷
期数:
2009年09期
页码:
11-14
栏目:
现代电子技术
出版日期:
2009-09-05

文章信息/Info

Title:
Anomaly detection of hyperspectral imagery based on background restrain and VCA
文章编号:
1009-671X(2009)09-0011-04
作者:
赵春晖王楠楠
哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨150001
Author(s):
ZHAO Chunhui WANG Nannan
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001,China
关键词:
高光谱图像目标检测顶点成分分析
Keywords:
hyperspectral imagery anomaly detection vertex component analysis
分类号:
TP212
DOI:
oi:10.3969/j.issn.1009-671X.2009.09.003
文献标志码:
A
摘要:
高光谱图像异常小目标检测数据量大、信息提取困难.文中提出了一种不需要先验信息并且计算复杂度较低的快速检测算法——基于背景抑制及顶点成分分析(EVCA)的异常小目标检测.利用高光谱图像端元是单形体顶点这一特性,在抑制背景后的图像上提取目标端元,并结合光谱匹配技术完成目标检测.为了验证新方法的有效性,与不经过背景抑制的VCA算法及传统检测算法进行了比较.实验结果表明,该算法不需要先验信息,体现了较好的检测效果.
Abstract:
In order to solve the problem of mass data and hard extraction of information in the anomaly detection of hyperspectral imagery, this paper presents a fast detection algorithm that has lower complexity of computation and does not need prior knowledge—anomaly detection of hyperspectral imagery based on background restrain and VCA (vertex component analysis). By making use of the characteristic that the high spectral image’s endmembers are the vertexes of single figure, this algorithm extracts endmembers from the image after restraining background, and detects the anomaly target by combining the spectrum matching technology. But the anomaly target to detect usually has low probability and is badly affected by the noise from background. So we first extract the information of background and use orthogonal projection to restrain it. The experiments show that this algorithm can improve the detection performance. 

参考文献/References:

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金资助项目(60672034);高等学校博士学科点基金资助项目(20060217021);黑龙江省自然科学基金资助项目(ZJG060601).
作者简介:赵春晖(1965-),男,教授,博士生导师,主要研究方向:信号处理,E-mail:zhaochunhui@hrbeu.edu.cn.
更新日期/Last Update: 2009-10-26