A 2D hyperspectral library of mineral reflectance, from 900 to 2500 nm.

ABSTRACT: Mineral identification using machine learning requires a significant amount of training data. We built a library of 2D hyperspectral images of minerals. The library contains reflectance images of 130 samples, of 76 distinct minerals, with more than 3.9 million data points. In order to produce this dataset, various well-characterized mineral samples were scanned, using a SPECIM Short Wave Infrared (SWIR) camera, which captures wavelengths from 900 to 2500 nm. Minerals were selected to represent all the mineral classes and the most common mineral occurrences. For each sample, the following data are provided: (a) At least one hyperspectral image of the sample, consisting of 256 wavelengths between 900 and 2500 nm. The raw data, the high dynamic range (HDR) image, and the masked HDR image are

SUBMITTER: Fasnacht L 

PROVIDER: S-EPMC6848079 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature