Camouflaged Target Detection Based on Snapshot Multispectral Imaging
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/19/3949 |
| _version_ | 1797515801789464576 |
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| author | Ying Shen Jie Li Wenfu Lin Liqiong Chen Feng Huang Shu Wang |
| author_facet | Ying Shen Jie Li Wenfu Lin Liqiong Chen Feng Huang Shu Wang |
| author_sort | Ying Shen |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T06:52:24Z |
| format | Article |
| id | doaj.art-b66ace6989ce47178a8a7713ee495559 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:52:24Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b66ace6989ce47178a8a7713ee4955592023-11-22T16:43:13ZengMDPI AGRemote Sensing2072-42922021-10-011319394910.3390/rs13193949Camouflaged Target Detection Based on Snapshot Multispectral ImagingYing Shen0Jie Li1Wenfu Lin2Liqiong Chen3Feng Huang4Shu Wang5School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaThe 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.https://www.mdpi.com/2072-4292/13/19/3949snapshot multispectral imagingcamouflaged target detectionCEMOTSUurban object-analysis |
| spellingShingle | Ying Shen Jie Li Wenfu Lin Liqiong Chen Feng Huang Shu Wang Camouflaged Target Detection Based on Snapshot Multispectral Imaging Remote Sensing snapshot multispectral imaging camouflaged target detection CEM OTSU urban object-analysis |
| title | Camouflaged Target Detection Based on Snapshot Multispectral Imaging |
| title_full | Camouflaged Target Detection Based on Snapshot Multispectral Imaging |
| title_fullStr | Camouflaged Target Detection Based on Snapshot Multispectral Imaging |
| title_full_unstemmed | Camouflaged Target Detection Based on Snapshot Multispectral Imaging |
| title_short | Camouflaged Target Detection Based on Snapshot Multispectral Imaging |
| title_sort | camouflaged target detection based on snapshot multispectral imaging |
| topic | snapshot multispectral imaging camouflaged target detection CEM OTSU urban object-analysis |
| url | https://www.mdpi.com/2072-4292/13/19/3949 |
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