Hyperspectral Band Selection via Rank Minimization

@article{Zhu2017HyperspectralBS,
  title={Hyperspectral Band Selection via Rank Minimization},
  author={Guokang Zhu and Yuancheng Huang and Shuiying Li and Jun Tang and Dong Liang},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2017},
  volume={14},
  pages={2320-2324}
}

• Guokang Zhu, Yuancheng Huang, +2 authors Dong Liang
• Published 2017 in IEEE Geoscience and Remote Sensing Letters
• DOI:10.1109/LGRS.2017.2763183

Band selection is an important preprocessing technique for hyperspectral imagery, through which a subset of critical and representative spectral bands can be selected from a raw image cube for compact yet effect representation. Among the valid selection strategies, performing band selection in an unsupervised manner is usually considered more general due to its application-independent characteristic. This letter proposed a novel unsupervised hyperspectral band selector that can capture the… CONTINUE READING

Save to Library

Create Alert

Cite

View on IEEE