Applying ordered statistic filters for point target detection in hyperspectral data

被引：5
|
作者：
Raviv, O [1 ]
Rotman, SR [1 ]
机构：
[1] Ben Gurion Univ Negev, Dept Elect & Comp Engn, IL-84105 Beer Sheva, Israel
来源：
SIGNAL AND DATA PROCESSING OF SMALL TARGETS 2003 | 2003年 / 5204卷
关键词：
hyperspectral imagery; point target detection;
D O I：
10.1117/12.503942
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, we apply higher ordered statistics filters to hyperspectral data to enable the detection of anomalous targets whose signatures are known. Each frame has subtracted from it an estimate based on an ordered statistics filter; the resulting frames are then combined optimally based on the covariance data of the cube and the spectral signature of the target. We show that the effect of the ordered statistic filter is to eliminate false alarms at edge points.
引用
收藏
页码：35 / 40
页数：6
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