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Extreme-constrained spatial-spectral corner detector for image-level hyperspectral image classification
Li, Yanshan1,2,6; Xu, Jianjie1; Xia, Rongjie1; Huang, Qinghua1,3,4; Xie, Weixin1; Li, Xuelong5; Huang, QH (reprint author), Shenzhen Univ, Coll Informat Engn, ATR Natl Key Lab Def Technol, Shenzhen 518060, Peoples R China.
作者部门光学影像学习与分析中心
2018-07-15
发表期刊PATTERN RECOGNITION LETTERS
ISSN0167-8655
卷号109页码:110-119
产权排序4
摘要As one type of local invariant feature, corner feature plays an important role in diverse applications such as: video mining, target detection, image classification, image retrieval, and image matching, etc. However, there are few studies on corner feature for hyperspectral image (HSI). Therefore, this paper proposes a novel corner feature for HSI named extreme-constrained spatial-spectral corner (ECSSC for short) and its corresponding detector. The definition of ECSSC is developed based on the definition of spectral-spatial interest point and the characteristic of HSI. Based on this definition, the detector of ECSSC is put forward and introduced in detail. Then, as an important application of ECSSC, an efficient framework for image-level HSI classification is designed based on ECSSC and parallel computation. The experimental results show that the proposed algorithm can detect abundant corner features with high repeatability rate from HSI and the accuracy of image-level HSI based on ECSSC is dramatically higher than that of the state of the art.
文章类型Article
学科领域Computer Science, Artificial Intelligence
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patrec.2018.03.022
收录类别SCI
关键词[WOS]FACE RECOGNITION ; FEATURE-EXTRACTION ; MODEL ; INFORMATION ; SATURATION ; REGRESSION ; KERNELS ; QUALITY
语种英语
WOS研究方向Computer Science
项目资助者National Natural Science Foundation of China(61771319 ; Natural Science Foundation of Guangdong Province(2017A030313343 ; Shenzhen Science and Technology Project(JCYJ20160520173822387 ; Project of Science and Technology Department of Guangdong Province(2014A050503020 ; Science and Technology Program of Guangzhou(201704020134) ; 61372007 ; 2017A030312006) ; JCYJ20160307143441261) ; 2016A010101021 ; 61571193) ; 2016A010101022 ; 2016A010101023)
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000434380800015
引用统计
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/30342
专题光学影像学习与分析中心
通讯作者Huang, QH (reprint author), Shenzhen Univ, Coll Informat Engn, ATR Natl Key Lab Def Technol, Shenzhen 518060, Peoples R China.
作者单位1.Shenzhen Univ, Coll Informat Engn, ATR Natl Key Lab Def Technol, Shenzhen 518060, Peoples R China
2.China Three Gorges Univ, Hubei Key Lab Intelligent Vis Based Monitoring Hy, Yichang 443002, Peoples R China
3.Northwestern Polytech Univ, Sch Mech Engn, Xian 710072, Shaanxi, Peoples R China
4.Northwestern Polytech Univ, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710072, Shaanxi, Peoples R China
5.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China
6.Shenzhen Univ, Coll Informat Engn, Guangdong Key Lab Intelligent Informat Proc, Shenzhen, Peoples R China
推荐引用方式
GB/T 7714
Li, Yanshan,Xu, Jianjie,Xia, Rongjie,et al. Extreme-constrained spatial-spectral corner detector for image-level hyperspectral image classification[J]. PATTERN RECOGNITION LETTERS,2018,109:110-119.
APA Li, Yanshan.,Xu, Jianjie.,Xia, Rongjie.,Huang, Qinghua.,Xie, Weixin.,...&Huang, QH .(2018).Extreme-constrained spatial-spectral corner detector for image-level hyperspectral image classification.PATTERN RECOGNITION LETTERS,109,110-119.
MLA Li, Yanshan,et al."Extreme-constrained spatial-spectral corner detector for image-level hyperspectral image classification".PATTERN RECOGNITION LETTERS 109(2018):110-119.
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