TARGET AND BACKGROUND SEPARATION IN HYPERSPECTRAL IMAGERY FOR AUTOMATIC TARGET DETECTION

被引：0
作者：
Bitar, Ahmad W. [1 ]
Cheong, Loong-Fah [2 ]
Ovarlez, Jean-Philippe [1 ,3 ]
机构：
[1] SONDRA Cent Supelec, Plateau Moulon, 3 Rue Joliot Curie, F-91190 Gif Sur Yvette, France
[2] NUS, Singapore, Singapore
[3] DEMR TSI, ONERA, Chemin Huniere, F-91120 Palaiseau, France
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年
关键词：
Hyperspectral target detection; target separation; low rank background HSI; sparse target HSI; DETECTION ALGORITHMS; MATCHED-FILTER; ESTIMATOR;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this paper, we propose a method for separating known targets of interests from the background in hyperspectral imagery. More precisely, we regard the given hyperspectral image (HSI) as being made up of the sum of low-rank background HSI and a sparse target HSI that contains the known targets based on a pre-learned target dictionary specified by the user. Based on the proposed method, two strategies are outlined and evaluated independently to realize the target detection on both synthetic and real experiments.
引用
收藏
页码：1598 / 1602
页数：5
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