NDLI: Camouflaged Target Detection Based on Snapshot Multispectral Imaging

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Camouflaged Target Detection Based on Snapshot Multispectral Imaging

Content Provider	MDPI
Author	Shen, Ying Li, Jie Lin, Wenfu Chen, Liqiong Huang, Feng Wang, Shu
Copyright Year	2021
Description	The spectral information contained in the hyperspectral images (HSI) distinguishes the intrinsic properties of a target from the background, which is widely used in remote sensing. However, the low imaging speed and high data redundancy caused by the high spectral resolution of imaging spectrometers limit their application in scenarios with the real-time requirement. In this work, we achieve the precise detection of camouflaged targets based on snapshot multispectral imaging technology and band selection methods in urban-related scenes. Specifically, the camouflaged target detection algorithm combines the constrained energy minimization (CEM) algorithm and the improved maximum between-class variance (OTSU) algorithm (t-OTSU), which is proposed to obtain the initial target detection results and adaptively segment the target region. Moreover, an object region extraction (ORE) algorithm is proposed to obtain a complete target contour that improves the target detection capability of multispectral images (MSI). The experimental results show that the proposed algorithm has the ability to detect different camouflaged targets by using only four bands. The detection accuracy is above 99%, and the false alarm rate is below 0.2%. The research achieves the effective detection of camouflaged targets and has the potential to provide a new means for real-time multispectral sensing in complex scenes.
Starting Page	3949
e-ISSN	20724292
DOI	10.3390/rs13193949
Journal	Remote Sensing
Issue Number	19
Volume Number	13
Language	English
Publisher	MDPI
Publisher Date	2021-10-02
Access Restriction	Open
Subject Keyword	Remote Sensing Snapshot Multispectral Imaging Camouflaged Target Detection Cem Otsu Urban Object-analysis
Content Type	Text
Resource Type	Article

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