UM
Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System
Kong, Yi; Wang, Xuesong; Cheng, Yuhu; Chen, C. L. Philip
2018-05
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:5
AbstractRecently, deep learning-based methods have drawn increasing attention in hyperspectral imagery (HSI) classification, due to their strong nonlinear mapping capability. However, these methods suffer from a time-consuming training process because of many network parameters. In this paper, the concept of broad learning is introduced into HSI classification. Firstly, to make full use of abundant spectral and spatial information of hyperspectral imagery, hierarchical guidance filtering is performing on the original HSI to get its spectral-spatial representation. Then, the class-probability structure is incorporated into the broad learning model to obtain a semi-supervised broad learning version, so that limited labeled samples and many unlabeled samples can be utilized simultaneously. Finally, the connecting weights of broad structure can be easily computed through the ridge regression approximation. Experimental results on three popular hyperspectral imagery datasets demonstrate that the proposed method can achieve better performance than deep learning-based methods and conventional classifiers.
Keywordhyperspectral imagery classification broad learning semi-supervised class-probability structure
DOI10.3390/rs10050685
URLView the original
Indexed BySCI
Language英语
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000435198400027
PublisherMDPI
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:11   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Kong, Yi,Wang, Xuesong,Cheng, Yuhu,et al. Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System[J]. REMOTE SENSING,2018,10(5).
APA Kong, Yi,Wang, Xuesong,Cheng, Yuhu,&Chen, C. L. Philip.(2018).Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System.REMOTE SENSING,10(5).
MLA Kong, Yi,et al."Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System".REMOTE SENSING 10.5(2018).
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