Semisupervised Pair-Wise Band Selection for Hyperspectral Images
文献类型：期刊论文
| 作者 | Bai, Jun ; Xiang, Shiming; Shi, Limin; Pan, Chunhong
|
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
 |
| 出版日期 | 2015-06-01 |
| 卷号 | 8期号:6页码:2798-2813 |
| 关键词 | Band selection classification hyperspecral remote sensing semisupervised |
| 英文摘要 | This paper proposes a new approach of band selection for classifying multiple objects in hyperspectral images. Different from traditional algorithms, we construct a semisupervised pair-wise band selection (PWBS) framework for this task, in which an individual band selection process is performed only for each pair of classes. First, the statistical parameters for spectral features of each class, including mean vectors and covariance matrices, are estimated by an expectation maximization approach in a semisupervised learning setting, where both labeled and unlabeled samples are employed for better performance. For each pair of classes, based on the estimated statistical parameters, Bhattacharyya distances between the two classes are calculated to evaluate all possible subsets of bands for classification. Second, as our proposed semisupervised framework, the PWBS followed by a binary classifier can be embedded into the semisupervised expectation maximization process to obtain posterior probabilities of samples on the selected bands. Finally, to evaluate the selected bands, all of the binary decisions obtained with multiple binary classifiers are finally fused together. Comparative experimental results demonstrate the validity of our proposed algorithm. The experimental results also prove that our band selection algorithm can perform well when the training set is very small. |
| WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
| 类目[WOS] | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
| 研究领域[WOS] | Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology |
| 关键词[WOS] | SUPPORT VECTOR MACHINES ; DIMENSIONALITY REDUCTION ; MORPHOLOGICAL PROFILES ; DISCRIMINANT-ANALYSIS ; CLASSIFICATION ; SVM ; INFORMATION ; PARAMETERS ; REGRESSION ; ALGORITHM |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000359264000042 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8902]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bai, Jun,Xiang, Shiming,Shi, Limin,et al. Semisupervised Pair-Wise Band Selection for Hyperspectral Images[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2015,8(6):2798-2813. |
| APA | Bai, Jun,Xiang, Shiming,Shi, Limin,&Pan, Chunhong.(2015).Semisupervised Pair-Wise Band Selection for Hyperspectral Images.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,8(6),2798-2813. |
| MLA | Bai, Jun,et al."Semisupervised Pair-Wise Band Selection for Hyperspectral Images".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 8.6(2015):2798-2813. |
入库方式： OAI收割
来源：自动化研究所
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