TY - JOUR
T1 - Compensation for subpixel roughness effects in thermal infrared images
AU - Danilina, Iryna
AU - Gillespie, Alan R.
AU - Balick, Lee
AU - Mushkin, Amit
AU - Smith, Matthew
AU - Blumberg, Dan
N1 - Funding Information: This work was funded by the US National Nuclear Security Administration, Office of Nonproliferation Technology Development, contract DE-FG52-08NA28772, and subcontract DE-AC52-06NA25396 with the Los Alamos National Laboratory.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - Emissivity spectra recovered from spectral radiance images may have lowered spectral contrast due to irradiance from nearby surface elements ('cavity effect'). For analysis based only on photointerpretation or Reststrahlen band identification, it is not always necessary to account for cavity effects, but for full spectral analysis it may be desirable. We present an approach to compensate thermal infrared (TIR) images for cavity radiation. This approach is based on optical estimates of subpixel surface roughness and estimation of cavity contribution for different natural surfaces using a TIR radiosity model. It was tested using tripod-mounted Hyper-Cam (Telops, Inc., Quebec City, Canada) hyperspectral TIR images of natural targets from the Mojave Desert, California, USA, along with centimetre-scale digital elevation models of similar targets measured by ground lidar. For remote subpixel roughness estimation, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) nadir- and aft-looking (27.6°) near-infrared (NIR) brightness ratios, as well as synthetic aperture radar (SAR) images calibrated to roughness root mean square (RMS), were used. The TIR compensation approach is adaptable for different spectral resolutions, including hyperspectral.
AB - Emissivity spectra recovered from spectral radiance images may have lowered spectral contrast due to irradiance from nearby surface elements ('cavity effect'). For analysis based only on photointerpretation or Reststrahlen band identification, it is not always necessary to account for cavity effects, but for full spectral analysis it may be desirable. We present an approach to compensate thermal infrared (TIR) images for cavity radiation. This approach is based on optical estimates of subpixel surface roughness and estimation of cavity contribution for different natural surfaces using a TIR radiosity model. It was tested using tripod-mounted Hyper-Cam (Telops, Inc., Quebec City, Canada) hyperspectral TIR images of natural targets from the Mojave Desert, California, USA, along with centimetre-scale digital elevation models of similar targets measured by ground lidar. For remote subpixel roughness estimation, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) nadir- and aft-looking (27.6°) near-infrared (NIR) brightness ratios, as well as synthetic aperture radar (SAR) images calibrated to roughness root mean square (RMS), were used. The TIR compensation approach is adaptable for different spectral resolutions, including hyperspectral.
UR - http://www.scopus.com/inward/record.url?scp=84873638353&partnerID=8YFLogxK
U2 - https://doi.org/10.1080/01431161.2012.716919
DO - https://doi.org/10.1080/01431161.2012.716919
M3 - Article
SN - 0143-1161
VL - 34
SP - 3425
EP - 3436
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 9-10
ER -