Calibration of a Hyper-Spectral Imaging System Using a Low-Cost Reference

In this paper, we present a hyper-spectral imaging system and practical calibration procedure using a low-cost calibration reference made of polytetrafluoroethylene. The imaging system includes a hyperspectral camera and an active source of illumination with a variable spectral distribution of intensity. The calibration reference is used to measure the relative reflectance of any material surface independent of the spectral distribution of light and camera sensitivity. Winter road conditions are taken as a test application, and several spectral images of snow, icy asphalt, dry asphalt, and wet asphalt were made at different exposure times using different illumination spectra. Graphs showing measured relative reflectance for different road conditions support the conclusion that measurements are independent of illumination. Principal component analysis of the acquired spectral data for road conditions shows well separated data clusters, demonstrating the system's suitability for material classification.

Automated summary

This study presents a hyper-spectral imaging system for measuring road conditions, using a low-cost calibration reference to measure relative reflectance of any material surface independent of spectral distribution and camera sensitivity. Results show that the acquired spectral data can effectively differentiate different road conditions, demonstrating the system's suitability for material classification.