HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy
Published in Scientific Data (Nature), 2023
The characterization of mineral samples through hyperspectral imaging has become increasingly important in geometallurgy. This work presents HIDSAG, a publicly available Hyperspectral Image Database for Supervised Analysis in Geometallurgy. The database contains hyperspectral images of mineral samples captured using SWIR (Short-wave infrared) and VNIR (visible and near-infrared) cameras, along with corresponding laboratory characterization data including geometallurgical properties and mineral occurrence measurements.
HIDSAG is designed to enable reproducible research in the field of mineral characterization from spectral data. The database includes comprehensive metadata and documentation to facilitate its use by the research community, supporting the development and benchmarking of new methods for geometallurgical estimation from hyperspectral data.
Recommended citation: Santibañez-Leal, F.A., Ehrenfeld, A., Garrido, F., Navarro, F., & Egaña, A. (2023). "HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy." Scientific Data, 10, 167.
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