Abstract
Results of a method of estimating index of refraction from passive, polarimetric hyperspectral imaging radiance measurements are presented. As off-nadir viewing hyperspectral imaging platforms gain prominence, estimating index of refraction, which is invariant to viewing angle, may prove advantageous to estimating the emissivity, which is not. Results show that index of refraction can be retrieved to within 8% rms error for fused silica and sapphire glass targets, while simultaneously estimating object temperature. The accuracy and self-consistency of this technique for estimating index of refraction are shown to compare favorably to the maximum smoothness temperature–emissivity separation algorithm. Additionally, the results show that atmospheric downwelling radiance can also be accurately estimated, to within the noise of the instrument, concurrently with index of refraction.
Highlights
One of the primary challenges in material classification and ID is dealing with target variability, that is, the same material producing different signatures based on scene conditions, illumination, viewing angle, etc
In the longwave infrared (LWIR), the at-sensor radiance comes from three sources: downwelling radiance reflecting off the target, radiance emitted by the target, and radiance emitted by the atmosphere along the line of sight
This work demonstrates that index of refraction, for specular reflectors, can be accurately retrieved from passive P-hyperspectral imaging (HSI) radiance measurements
Summary
One of the primary challenges in material classification and ID is dealing with target variability, that is, the same material producing different signatures based on scene conditions, illumination, viewing angle, etc. This paper will deal primarily with the variability due to viewing angle and how estimating index of refraction, in place of emissivity, may be advantageous in certain scenarios. With additional emphasis being placed on sensing within A2/AD environments, off-nadir viewing sensors and algorithms to process data from these platforms are becoming increasingly important. When dealing with these oblique viewing geometries, the target variability due to the viewing angle of the sensor relative to the target’s surface normal can no longer be ignored. A fitting routine is developed using spectrally resolved polarimetric radiance measurements, often from multiple viewing geometries, to solve for index of refraction, surface temperature, and downwelling radiance. Of refraction is estimated, and, present some results as well as a comparison with a TES algorithm
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