Temperature emissivity separation using optimized atmospheric water band regions

Emissivity is the common space used to analyze longwave infrared (LWIR) data. For this analysis, data are collected using a Designs and Prototypes (D&P) Model 102 field portable Fourier transform infrared (FTIR) spectrometer using a Michelson interferometer. The interferograms are transformed into radiance space and calibrated with known cold and warm blackbody measurements. The spectral emissivity at each wavelength is derived from the measured radiance data. To perform the emissivity calculation surface temperature of the material of interest (MOI) must be known; however, the true surface temperature is challenging to acquire while in the field due to the dynamic nature of the environment. Unknown surface temperature and unknown spectral emissivity leads to systems of equations issues. A temperature emissivity separation (TES) algorithm is used to determine the optimal surface temperature, which aids in determining the spectral emissivity of the MOI. The Hybrid method proposed in this paper implements optimized contiguous water regions in the longwave wavelengths to include 7.563-7.663, 7.714-7.800, 7.853-7.907 and 13.51-13. 67 micrometers (μm). These bands represent spectral features in water that are not optically thick in the atmosphere, and are chosen because they do not overlap with features of most MOIs. The spectral emissivity is solved for using all the wavelength bands defined in the spectral regions for a range of temperatures spanning from 10 to 60° C. Each calculated emissivity spectra is subjected to a high-pass filter, and the sum of the squares of the filtered emissivity spectra is calculated. A temperature is selected that produces smoothest calculated emissivity curve. The smoothest line is optimal because the water region is assumed to be flat, and blackbody-like with an emissivity near one. The resulting temperature values for each of the four spectral regions are compared against one another. If the standard deviation of the four temperature values is below one, the mean is selected as the best surface temperature; otherwise, the median is selected as the best surface temperature. For initial assessment of this proposed TES method, six MOIs with unique features in the LWIR wavelengths were analyzed; concrete, cotton, Pyrex (glass), sulfur, sand and polyethylene. For the majority of the MOIs the blackbody spectrum calculated using the optimal temperature determined by the Hybrid algorithm overlaid exactly on the measured surface leaving radiance spectrum corresponding to the MOI. MOIs with spectral features in the longer wavelengths of the LWIR, specifically the sulfur and the polyethylene, had standard deviations above one, skewed by the optimal temperature predicted for the 13.51-13.67 μm region. When the outlier temperature is removed using the median to derive optimal temperature of the MOI the results were consistent with the expected emissivity. The Hybrid emissivity spectra are also compared against two other known TES methods and the results indicate improved and accurate prediction of emissivity, specifically in the outer regions of the LWIR wavelengths.