Building a Hyperspectral Library and its Incorporation into Sparse Unmixing for Mineral Identification - BRGM - Bureau de recherches géologiques et minières Access content directly
Conference Papers Year : 2018

Building a Hyperspectral Library and its Incorporation into Sparse Unmixing for Mineral Identification

Anne Salaün
  • Function : Author
Cedric Duee
Thomas Wallmach
  • Function : Author
Monique Le Guen
  • Function : Author

Abstract

The objective of the SOLSA project (EU-H2020) is to develop an analytical expert system for on-line-on-mine-real-time mineralogical and geochemical analyses on sonic drill cores. As one aspect of the system, this paper presents the building of the hyperspectral library and its incorporation into sparse unmixing techniques for mineral identification. Twenty seven spectra representing 14 minerals have been collected for the library. Three sparse unmixing techniques have been investigated and evaluated using simulated data generated from our hyperspectral library, and real hyperspectral data acquired from a serpentinized harzburgite sample. Among the three techniques, the collaborative sparse unmixing by variable splitting and augmented Lagrangian (CLSUnSAL) method provided the best accurate results on the simulated data. In addition, the results of the CLSUnSAL method show high correlation with that of the QEMSCAN® analysis on the harzburgite hyperspectral data.
No file

Dates and versions

hal-02734395 , version 1 (02-06-2020)

Identifiers

Cite

Thanh Bui, Beate Orberger, Simon Blancher, Ali Mohammad-Djafari, Henry Pilliere, et al.. Building a Hyperspectral Library and its Incorporation into Sparse Unmixing for Mineral Identification. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Jul 2018, Valencia, France. pp.4261-4264, ⟨10.1109/IGARSS.2018.8519131⟩. ⟨hal-02734395⟩
114 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More