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

Muhammad Saad Shaikh,Johan Casselgren,Keyvan Jaferzadeh,Benny Thörnberg

doi:10.3390/s21113738

Abstract

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.

Highlights

Spectral distributions of light reflected in the surface of the calibration reference WR(λ) were measured at the same location as the corresponding road condition without moving the experimental setup
It is shown that the relative reflectance of a surface can be measured independently of the spectral distribution of both light intensity and sensitivity of a hyperspectral camera
Measurements of relative reflectance assume the use of specific reference material during the calibration procedure

Summary

Introduction

Spectral Imaging is a technique in which spectral information is shown as the third dimension of a two-dimensional spatial image (sometimes called a cube image). It was first proposed for remote sensing of Earth in 1985 [1]. The illumination can be ambient light from the sun or an active source of illumination such as halogen lamps, xenon lamps, or LEDs. The reflection of light is a process that creates unique spectral signatures depending on the material composition of the reflecting surface [7]. Spectral imaging allows for the recording of unique spectral signatures in two dimensions such that the use of a trained classifier can determine the surface material at each individual pixel [8]

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