Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser
Hyperspectral imaging (HSI) technology is able to provide fine spectral and spatial information of objects. It has the ability to discriminate materials and thereby has been used in a wide range of areas. However, traditional HSI strongly depends on the sunlight and hence is restricted to daytime. I...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/9/3088 |
id |
doaj-7d1e13cbff724662b97b1c3bb81b55dd |
---|---|
record_format |
Article |
spelling |
doaj-7d1e13cbff724662b97b1c3bb81b55dd2020-11-25T02:22:56ZengMDPI AGApplied Sciences2076-34172020-04-01103088308810.3390/app10093088Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum LaserYu Liu0Zilong Tao1Jun Zhang2Hao Hao3Yuanxi Peng4Jing Hou5Tian Jiang6College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, ChinaCollege of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, ChinaCollege of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, ChinaHyperspectral imaging (HSI) technology is able to provide fine spectral and spatial information of objects. It has the ability to discriminate materials and thereby has been used in a wide range of areas. However, traditional HSI strongly depends on the sunlight and hence is restricted to daytime. In this paper, a visible/near-infrared active HSI classification method illuminated by a visible/near-infrared supercontinuum laser is developed for spectra detection and objects imaging in the dark. Besides, a deep-learning-based classifier, hybrid DenseNet, is created to learn the feature representations of spectral and spatial information parallelly from active HSI data and is used for the active HSI classification. By applying the method to a selection of objects in the dark successfully, we demonstrate that with the active HSI classification method, it is possible to detect objects of interest in practical applications. Correct active HSI classification of different objects further supports the viability of the method for camouflage detection, biomedical alteration detection, cave painting mapping and so on.https://www.mdpi.com/2076-3417/10/9/3088active hyperspectral imagingsupercontinuum laserclassificationdeep-learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yu Liu Zilong Tao Jun Zhang Hao Hao Yuanxi Peng Jing Hou Tian Jiang |
spellingShingle |
Yu Liu Zilong Tao Jun Zhang Hao Hao Yuanxi Peng Jing Hou Tian Jiang Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser Applied Sciences active hyperspectral imaging supercontinuum laser classification deep-learning |
author_facet |
Yu Liu Zilong Tao Jun Zhang Hao Hao Yuanxi Peng Jing Hou Tian Jiang |
author_sort |
Yu Liu |
title |
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser |
title_short |
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser |
title_full |
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser |
title_fullStr |
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser |
title_full_unstemmed |
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser |
title_sort |
deep-learning-based active hyperspectral imaging classification method illuminated by the supercontinuum laser |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2020-04-01 |
description |
Hyperspectral imaging (HSI) technology is able to provide fine spectral and spatial information of objects. It has the ability to discriminate materials and thereby has been used in a wide range of areas. However, traditional HSI strongly depends on the sunlight and hence is restricted to daytime. In this paper, a visible/near-infrared active HSI classification method illuminated by a visible/near-infrared supercontinuum laser is developed for spectra detection and objects imaging in the dark. Besides, a deep-learning-based classifier, hybrid DenseNet, is created to learn the feature representations of spectral and spatial information parallelly from active HSI data and is used for the active HSI classification. By applying the method to a selection of objects in the dark successfully, we demonstrate that with the active HSI classification method, it is possible to detect objects of interest in practical applications. Correct active HSI classification of different objects further supports the viability of the method for camouflage detection, biomedical alteration detection, cave painting mapping and so on. |
topic |
active hyperspectral imaging supercontinuum laser classification deep-learning |
url |
https://www.mdpi.com/2076-3417/10/9/3088 |
work_keys_str_mv |
AT yuliu deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT zilongtao deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT junzhang deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT haohao deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT yuanxipeng deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT jinghou deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser AT tianjiang deeplearningbasedactivehyperspectralimagingclassificationmethodilluminatedbythesupercontinuumlaser |
_version_ |
1724861007877111808 |