OPTIONS FOR SOLID POINT TARGET DETECTION IN HYPERSPECTRAL DATA

被引：0
|
作者：
Yurkovetsky, Eliad [1 ]
Rotman, Stanley R. [1 ]
机构：
[1] Ben Gurion Univ Negev, Sch Elect & Comp Engn, Beer Sheva, Israel
来源：
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2023年
关键词：
hyperspectral; point target detection; covariance matrix;
D O I：
10.1109/IGARSS52108.2023.10281974
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Adaptive target detection algorithms need to estimate parameters before the actual calculation of the metric for target detection. For solid subpixel targets in hyperspectral data, we consider two algorithms for effective detection. The first algorithm uses explicitly only background estimation; the second estimates both the background and the target fraction in the pixel. We compare the performance of each algorithm; we also consider the need to alter the estimated covariance matrix based on the estimated target fraction.
引用
收藏
页码：2270 / 2273
页数：4
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