Scene analysis and detection in thermal infrared remote sensing using independent component analysis

被引：8
|
作者：
Foy, BR [1 ]
Theiler, J [1 ]
机构：
[1] Los Alamos Natl Lab, Los Alamos, NM 87545 USA
来源：
INDEPENDENT COMPONENT ANALYSES, WAVELETS, UNSUPERVISED SMART SENSORS, AND NEURAL NETWORKS II | 2004年 / 5439卷
关键词：
remote sensing; hyperspectral imaging; lidar; ICA; chemical sensing;
D O I：
10.1117/12.542442
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Independent Component Analysis can be used to analyze cluttered scenes from remote sensing imagery and to detect objects. We show examples in the thermal infrared spectral region (8-12 mum) using both passive hyperspectral data and active multispectral data. The examples are from actual field data and computer simulations. ICA isolates spectrally distinct objects with nearly one-to-one correspondence with the independent component basis functions, making it useful for modeling the clutter in typical scenes. We show examples of chemical plume detection in real and simulated data.
引用
收藏
页码：131 / 139
页数：9
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