Semisupervised Hyperspectral Image Classification via Discriminant Analysis and Robust Regression
Cheng, Guangliang; Zhu, Feiyun; Xiang, Shiming; Wang, Ying; Pan, Chunhong
2016-02-01
发表期刊IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷号9期号:2页码:595-608
文章类型Article
摘要In recent years, hyperspectral image classification (HSIC) has received increasing attention in a wide range of hyperspectral applications. It is still very challenging due to the following factors: 1) there are not enough labeled samples; 2) the images are easy to be polluted by outlier channels; and 3) different objects may have similar spectra. Considering these three factors, we propose a novel semisupervised HSIC method, which is constructed on discriminant analysis and robust regression (DARR). Specifically, a regression-based semisupervised technique is employed by not only exploiting the rich information in labeled samples, but also taking advantage of abundant unlabeled ones. In this way, the true data distribution can be obtained accurately. Then, we introduce a robust adaptive loss function to measure the representation loss. As a result, it can greatly relieve the side effects of outlier channels. Finally, to increase discriminating power of our approach for different objects, we utilize the pairwise constraints to incorporate the discriminant information among labeled samples. Through these constraints, the same-category samples are projected to be close to each other, while the different-category samples are as far apart as possible. The above three components can be integrated into a graph-based objective function, whose optimization is systematically provided. Extensive experiments on four data sets demonstrate that our method achieves higher quantitative results, as well as more satisfactory visual performances by comparing with state-of-the-art methods and using different parameter settings.
关键词Discriminant Analysis Hyperspectral Image Classification (Hsic) Pairwise Constraints Robust Regression Semisupervised Learning (Ssl)
WOS标题词Science & Technology ; Technology ; Physical Sciences
DOI10.1109/JSTARS.2015.2471176
关键词[WOS]SUPPORT VECTOR MACHINES ; REMOTE-SENSING IMAGES ; MORPHOLOGICAL ATTRIBUTE PROFILES ; HIGH-RESOLUTION IMAGES ; SPATIAL CLASSIFICATION ; SEGMENTATION ; FUSION
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61305049 ; 91338202 ; 61375024 ; 91438105)
WOS研究方向Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000370877600005
引用统计
被引频次:9[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11354
专题模式识别国家重点实验室_先进数据分析与学习
作者单位Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
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GB/T 7714
Cheng, Guangliang,Zhu, Feiyun,Xiang, Shiming,et al. Semisupervised Hyperspectral Image Classification via Discriminant Analysis and Robust Regression[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2016,9(2):595-608.
APA Cheng, Guangliang,Zhu, Feiyun,Xiang, Shiming,Wang, Ying,&Pan, Chunhong.(2016).Semisupervised Hyperspectral Image Classification via Discriminant Analysis and Robust Regression.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,9(2),595-608.
MLA Cheng, Guangliang,et al."Semisupervised Hyperspectral Image Classification via Discriminant Analysis and Robust Regression".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 9.2(2016):595-608.
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