Projection-Based NMF for Hyperspectral Unmixing
文献类型：期刊论文
| 作者 | Yuan, Yuan ; Feng, Yachuang; Lu, Xiaoqiang
|
| 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:2632-2643 |
| 关键词 | Hyperspectral unmixing nonnegative matrix factorization (NMF) spectral library subspace projection |
| 英文摘要 | as a widely concerned research topic, many advanced algorithms have been proposed for hyperspectral unmixing. however, they may fail to accurately identify endmember signatures when coming across insufficient spatial resolution. to deal with this problem, an algorithm based on semisupervised linear sparse regression is proposed, in which unmixing procedure is reduced to seeking an optimal subset from the spectral library to best model mixed pixels in the scene. however, the number of the spectra with nonzero abundance is much more than that of the true endmember signatures. furthermore, the selection of library spectra as endmember signatures is undesirable due to the divergent imaging conditions. in this paper, a novel projection-based nonnegative matrix factorization (nmf) (pnmf) algorithm is proposed by importing spectra library into the nmf framework. the main novelties of this paper are listed as follows. 1) by introducing the spectral library, the extraction of endmember signatures is no longer restricted by spatial resolution. 2) related spectra are selected and projected onto a subspace containing the endmember signatures. so that the number of endmember signatures is controlled by dimension of the subspace. 3) in pnmf, the endmember signatures are adaptively generated from the spectral library, and are matched with the observed hyperspectral images. this overcomes the difficulty caused by diverse imaging conditions, and makes the proposed algorithm more practical for real applications. the experimental results, conducted on both synthetic and real hyperspectral data, illustrate the advantages of the proposed algorithm when compared with the state-of-the-art algorithms. |
| 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] | nonnegative matrix factorization ; spectral mixture analysis ; volume simplex analysis ; material quantification ; endmember extraction ; component analysis ; fast algorithm ; imagery ; regularization ; sparsity |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000359264000028 |
| 公开日期 | 2015-09-15 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/25288]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710119, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yuan, Yuan,Feng, Yachuang,Lu, Xiaoqiang. Projection-Based NMF for Hyperspectral Unmixing[J]. ieee journal of selected topics in applied earth observations and remote sensing,2015,8(6):2632-2643. |
| APA | Yuan, Yuan,Feng, Yachuang,&Lu, Xiaoqiang.(2015).Projection-Based NMF for Hyperspectral Unmixing.ieee journal of selected topics in applied earth observations and remote sensing,8(6),2632-2643. |
| MLA | Yuan, Yuan,et al."Projection-Based NMF for Hyperspectral Unmixing".ieee journal of selected topics in applied earth observations and remote sensing 8.6(2015):2632-2643. |
入库方式： OAI收割
来源：西安光学精密机械研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。