Airborne Hyperspectral Imagery for Band Selection Using Moth–Flame Metaheuristic Optimization
In this research, we study a new metaheuristic algorithm called Moth–Flame Optimization (MFO) for hyperspectral band selection. With the hundreds of highly correlated narrow spectral bands, the number of training samples required to train a statistical classifier is high. Thus, the problem is to sel...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-04-01
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Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/8/5/126 |