Hyperspectral imaging of minerals in the longwave infrared: the use of laboratory directional-hemispherical reference measurements for field exploration data

Abstract

Hyperspectral imaging (HSI) continues to grow as a method for remote detection of vegetation, materials, minerals, and pure chemicals. We have used a longwave infrared (7.7 to 11.8 μm) imaging spectrometer in a static outdoor experiment to collect HSI data from 24 minerals and background materials to determine the efficacy with which HSI can remotely detect and distinguish both pure minerals and mineral mixtures at a 45-deg tilt angle relative to ground using two different backgrounds. Measurements were obtained separately for the minerals and materials mounted directly on both a bare plywood board and a board coated with aluminum foil: 19 powders (3 mixtures and 16 pure mineral powders) held in polyethylene bottle lids as well as five samples in rock form were taped directly to the boards. The primary goal of the experiment was to demonstrate that a longwave infrared library of solids and minerals collected as directional-hemispherical reflectance spectra in the laboratory could be used directly for HSI field identification along with simple algorithms for a rapid survey of the target materials. Prior to the experiment, all 24 mineral/inorganic samples were measured in the laboratory using a Fourier transform infrared spectrometer equipped with a gold-coated integrating sphere; the spectra were assimilated as part of a larger reference library of 21 pure minerals, 3 mixtures, and the polyethylene lid. Principal component analysis with mean-centering was used in an exploratory analysis of the HSI images and showed that, for the aluminum-coated board, the first principal component captured the difference between the signal that resembled a blackbody and the highly reflective aluminum background. In contrast, the second, third, and fourth principal components were able to discriminate the materials including phosphates, silicates, carbonates, and the mixtures. Results from generalized least squares target detection clearly showed that laboratory reference spectra of minerals could be utilized as targets with high fidelity for field detection.

Infrared Optical Constants from Pressed Pellets of Powders: I. Improved n and k Values of (NH4)2SO4 from Single-Angle Reflectance

“…9,51 Conclusion Laboratory, industrial, and standoff IR spectroscopies continue their exponential growth. 52,53 It has already been demonstrated 54 that laboratory reference data can readily be used for field detection of both solids and liquids, as well as gases 55 but increasingly the n/k vectors are used for modeling 5,56 the target signal both for liquids 4 and solids. 54 Obtaining n/k for solids is more challenging, and one goal of this study was thus to (determine how to) prepare pellets with high surface smoothness, since the single-angle method measures only specular reflectance.…”

Improved Infrared Optical Constants from Pressed Pellets: II. Ellipsometric n and k Values for Ammonium Sulfate with Variability Analysis

“…Stand-off detection of chemicals deposited on substrates is an active area of research. [1][2][3][4] These techniques often measure the reflectance in the infrared (IR) spectral region using either passive or active detection. The IR enables higher sensitivity and selectivity due to the natural frequencies of the strong fundamental absorption features for a wide range of species.…”

“…This library often incorporates reference spectra that have been measured in a laboratory for the bulk material. 4 However, research has shown that morphological phenomena, e.g., layer thickness, 5 particle size, [6][7][8] etc., can influence the IR reflectance and emission spectra. A single reference spectrum of a pure chemical can thus be insufficient since the material needs to be recorded under similar morphological conditions as the in situ data.…”

Improving hyperspectral sub-pixel target detection in multiple target signatures using a revised replacement signal model

“…In this regard, the one-step generalized likelihood ratio test has recently been extended for sub-pixel target detection based on the replacement signal model . The sub-pixel target detection is important in many applications, such as battleground reconnaissance (Kumar & Ghosh, 2017), monitoring of mineral material (Myers et al, 2019), and so on.…”