UM
Spectral-Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification
Qin A.2; Shang Z.2; Tian J.1; Wang Y.3; Zhang T.2; Tang Y.Y.1
2019-02-01
Source PublicationIEEE Geoscience and Remote Sensing Letters
ISSN1545598X
Volume16Issue:2Pages:241-245
AbstractCollecting labeled samples is quite costly and time-consuming for hyperspectral image (HSI) classification task. Semisupervised learning framework, which combines the intrinsic information of labeled and unlabeled samples, can alleviate the deficient labeled samples and increase the accuracy of HSI classification. In this letter, we propose a novel semisupervised learning framework that is based on spectral-spatial graph convolutional networks ( \text{S}^{2} GCNs). It explicitly utilizes the adjacency nodes in graph to approximate the convolution. In the process of approximate convolution on graph, the proposed method makes full use of the spatial information of the current pixel. The experimental results on three real-life HSI data sets, i.e., Botswana Hyperion, Kennedy Space Center, and Indian Pines, show that the proposed \text{S}^{2} GCN can significantly improve the classification accuracy. For instance, the overall accuracy on Indian data is increased from 66.8% (GCN) to 91.6%.
KeywordGraph convolutional hyperspectral image (HSI) classification neural network semisupervised learning
DOI10.1109/LGRS.2018.2869563
URLView the original
Language英語
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Universidade de Macau
2.Chongqing University
3.Chengdu University
Recommended Citation
GB/T 7714
Qin A.,Shang Z.,Tian J.,et al. Spectral-Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification[J]. IEEE Geoscience and Remote Sensing Letters,2019,16(2):241-245.
APA Qin A.,Shang Z.,Tian J.,Wang Y.,Zhang T.,&Tang Y.Y..(2019).Spectral-Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification.IEEE Geoscience and Remote Sensing Letters,16(2),241-245.
MLA Qin A.,et al."Spectral-Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification".IEEE Geoscience and Remote Sensing Letters 16.2(2019):241-245.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Qin A.]'s Articles
[Shang Z.]'s Articles
[Tian J.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Qin A.]'s Articles
[Shang Z.]'s Articles
[Tian J.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Qin A.]'s Articles
[Shang Z.]'s Articles
[Tian J.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.