Improved ISOMAP algorithm for anomaly detection in hyperspectral images

被引：1
|
作者：
Wang, Liangliang [1 ]
Li, Zhiyong [1 ]
Sun, Jixiang [1 ]
机构：
[1] Natl Univ Def Technol, Sch Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
来源：
FOURTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2011): MACHINE VISION, IMAGE PROCESSING, AND PATTERN ANALYSIS | 2012年 / 8349卷
关键词：
manifold learning; ISOMAP; anomaly detection; hyperspectral; RX; spectrum ananlysis;
D O I：
10.1117/12.920078
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, ISOMAP algorithm is applied into anomaly detection on the basis of feature analysis in hyperspectral images. Then an improved ISOMAP algorithm is developed against the limitation existed in ISOMAP algorithm. The improved ISOMAP algorithm selects neighborhood according to spectral angel, thus avoiding the instability of the neighborhood in the high-dimension spectral space. Experimental results show the effectiveness of the algorithm in improving the detection performance.
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页数：5
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