Subpixel roughness effects in spectral thermal infrared emissivity images

Emissivity spectra recovered from spectral radiance images may have lowered spectral contrast due to irradiance from nearby surface elements (ldquocavity effectrdquo). For analyses based only on photointerpretation or Reststrahlen band identification, it is not always necessary to account for cavity effects, but for full spectral analyses, including spectral unmixing, it may be desirable. We present a method that is under development for compensating thermal infrared images for cavity radiation based on optical estimates of surface roughness and model inversion for percent cavity contribution. The approach is adaptable for different spectral resolutions, including hyperspectral. It will be tested on tripod-mounted Telops HyperCam hyperspectral thermal-infrared images of natural targets, LiDAR DEMs of similar targets, and optical estimates of shadowing, related to roughness.