BAYESIAN NON-PARAMETRIC DETECTOR BASED ON THE REPLACEMENT MODEL

被引：2
|
作者：
Matteoli, Stefania [1 ]
Diani, Marco [2 ]
Corsini, Giovanni [3 ]
机构：
[1] CNR, Inst Elect Comp & Telecommun Engn IEIIT, Via G Caruso 16, I-56122 Pisa, Italy
[2] Italian Naval Acad, Viale Italia 72, I-57127 Livorno, Italy
[3] Univ Pisa, Dept Informat Engn, Via G Caruso 16, I-56122 Pisa, Italy
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
关键词：
Hyperspectral; Target Detection; Bayes; non-parametric; replacement model;
D O I：
10.1109/IGARSS46834.2022.9883554
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
A Bayesian Likelihood Ratio Test (LRT) detector is analytically derived here for the replacement target model and using the non-parametric variable-bandwidth kernel density estimator to model the hyperspectral background. The detector is compared to the recent Generalized LRT detector, based on the same non-parametric model for the background. Experimental results obtained on two hyperspectral sub-pixel target detection scenarios reveal the great potential of the proposed detector and set the basis for future investigations.
引用
收藏
页码：871 / 874
页数：4
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