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Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking
Wang, Qi1; Lin, Jianzhe2; Yuan, Yuan2
Department光学影像学习与分析中心
2016-06
Source PublicationIEEE Transactions on Neural Networks and Learning Systems
ISSN2162237X
Volume27Issue:6Pages:1279-1289
Contribution Rank2
AbstractSaliency detection has been a hot topic in recent years, and many efforts have been devoted in this area. Unfortunately, the results of saliency detection can hardly be utilized in general applications. The primary reason, we think, is unspecific definition of salient objects, which makes that the previously published methods cannot extend to practical applications. To solve this problem, we claim that saliency should be defined in a context and the salient band selection in hyperspectral image (HSI) is introduced as an example. Unfortunately, the traditional salient band selection methods suffer from the problem of inappropriate measurement of band difference. To tackle this problem, we propose to eliminate the drawbacks of traditional salient band selection methods by manifold ranking. It puts the band vectors in the more accurate manifold space and treats the saliency problem from a novel ranking perspective, which is considered to be the main contributions of this paper. To justify the effectiveness of the proposed method, experiments are conducted on three HSIs, and our method is compared with the six existing competitors. Results show that the proposed method is very effective and can achieve the best performance among the competitors. © 2012 IEEE.
KeywordImage Classification Spectroscopy Vector Spaces
DOI10.1109/TNNLS.2015.2477537
Indexed ByEI
Language英语
Citation statistics
Cited Times:198[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/28252
Collection光学影像学习与分析中心
Affiliation1.School of Computer Science, Center Magery Analysis and Learning, Northwestern Polytechnical University, Xian; 710072, China
2.Center for Optical Imagery Analysis and Learning, State Key Laboratory of Transient Optics and Photonics, Chinese Academy of Sciences, Xian; 710119, China
Recommended Citation
GB/T 7714
Wang, Qi,Lin, Jianzhe,Yuan, Yuan. Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking[J]. IEEE Transactions on Neural Networks and Learning Systems,2016,27(6):1279-1289.
APA Wang, Qi,Lin, Jianzhe,&Yuan, Yuan.(2016).Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking.IEEE Transactions on Neural Networks and Learning Systems,27(6),1279-1289.
MLA Wang, Qi,et al."Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking".IEEE Transactions on Neural Networks and Learning Systems 27.6(2016):1279-1289.
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