[The correlation based mid-infrared temperature and emissivity separation algorithm].

Temperature and emissivity separation is the key problem in infrared remote sensing. Based on the analysis of the relationship between the atmospheric downward radiance and surface emissivity containing atmosphere residue without the effects of sun irradiation, the present paper puts forward a temperature and emissivity separation algorithm for the ground-based mid-infrared hyperspectral data. The algorithm uses the correlation between the atmospheric downward radiance and surface emissivity containing atmosphere residue as a criterion to optimize the surface temperature, and the correlation between the atmospheric downward radiance and surface emissivity containing atmosphere residue depends on the bias between the estimated surface temperature and true surface temperature.