A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing

@article{Ma2014ASP,
  title={A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing},
  author={Wing-Kin Ma and Josx00E9 M. Bioucas-Dias and Tsung-Han Chan and Nicolas Gillis and Paul D. Gader and Antonio J. Plaza and Arul-Murugan Ambikapathi and Chong-Yung Chi},
  journal={IEEE Signal Processing Magazine},
  year={2014},
  volume={31},
  pages={67-81}
}
Blind hyperspectral unmixing (HU), also known as unsupervised HU, is one of the most prominent research topics in signal processing (SP) for hyperspectral remote sensing [1], [2]. Blind HU aims at identifying materials present in a captured scene, as well as their compositions, by using high spectral resolution of hyperspectral images. It is a blind source separation (BSS) problem from a SP viewpoint. Research on this topic started in the 1990s in geoscience and remote sensing [3]-[7], enabled… CONTINUE READING
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N-FINDR: An algorithm for fast autonomous spectral endmember determination in hyperspectral data

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