Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery
文献类型：期刊论文
| 作者 | Zhuang, Lina1; Zhang, Bing1; Gao, Lianru1; Li, Jun1; Plaza, Antonio1 |
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
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| 出版日期 | 2015 |
| 卷号 | 8期号:6(SI)页码:16293-16314 |
| 关键词 | Endmember variability hyperspectral imaging normal compositional model (NCM) normal endmember spectral unmixing (NESU) particle swarm optimization (PSO) spectral unmixing |
| 通讯作者 | Gao, LR (reprint author), Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China. |
| 英文摘要 | The normal compositional model (NCM) has been introduced to characterize mixed pixels in hyperspectral images, particularly when endmember variability needs to be considered in the unmixing process. Each pixel is modeled as a linear combination of endmembers, which are treated as Gaussian random variables in order to capture such spectral variability. Since the combination coefficients (i.e., abundances) and the endmembers are unknown variables at the same time in the NCM, the parameter estimation is more difficult in comparison with conventional approaches. In order to address this issue, we propose a new Bayesian method, termed normal endmember spectral unmixing (NESU), for improved parameter estimation in this context. It considers the endmembers as known variables (resulting from the extraction of endmember bundles), then performs optimal estimations of the remaining unknown parameters, i.e., the abundances, using Bayesian inference. The particle swarm optimization (PSO) technique is adopted to estimate the optimal values of abundances according to their posterior probabilities. The performance of the proposed algorithm is evaluated using both synthetic and real hyperspectral data. The obtained results demonstrate that the proposed method leads to significant improvements in terms of unmixing accuracies. |
| 研究领域[WOS] | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000359264000025 |
| 公开日期 | 2015-01-07 |
| 版本 | 出版稿 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/37504]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Zhuang, Lina 2.Zhang, Bing 3.Gao, Lianru] Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China 4.[Zhuang, Lina] Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.[Li, Jun] Sun Yat Sen Univ, Guangdong Key Lab Urbanizat & Geosimulat, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China 6.[Plaza, Antonio] Univ Extremadura, Hyperspectral Comp Lab, Dept Technol Comp & Commun, Cacerres 10071, Spain |
| 推荐引用方式 GB/T 7714 | Zhuang, Lina,Zhang, Bing,Gao, Lianru,et al. Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2015,8(6(SI)):16293-16314. |
| APA | Zhuang, Lina,Zhang, Bing,Gao, Lianru,Li, Jun,&Plaza, Antonio.(2015).Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,8(6(SI)),16293-16314. |
| MLA | Zhuang, Lina,et al."Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 8.6(SI)(2015):16293-16314. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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