Jabar Saydi - Physics and laser research center of Imam Hosein compressive University and laser&optics research association;Young Research and Elit Club,East Tehran Branch, Islamic Azad University, Tehran,Iran
Javad Khalilzadeh - Physics and laser research center of Imam Hosein compressive University and laser&optics research association;
Safa Khazaei - Faculty of passive defense, Imam Hosein compressive University, Tehran, Iran;
Mehdi moameni - Faculty of Engineering, Isfahan University, Isfahan, Iran;

Emissive Empirical Line Method (EELM) estimates atmospheric transmission, emissivity and upwelling radiance using only the scene data. The EELM derive transmission, emissivity and upwelling radiance for thermal infrared HSI data. EELM is similar in concept to the empirical line method (ELM) algorithm commonly applied to visible/near-infrared to long wave infrared spectral imagery. Interpretation of surface radiation characteristics by overhead hyperspectral imagery often requires a compensation of the measured radiance data for the absorption and emission effects of the intervening atmosphere. We describe a procedure that accounts for these effects by direct use of the hyperspectral radiance data without recourse to ancillary meteorological data or atmospheric modeling. This in-scene atmospheric compensation procedure is applicable to a broad class of problems. The present work concerns terrestrial surface characterization by remote sensing in the atmospheric window band (1–14 μm). A complete EELM analysis is carried out in two steps. In the first step, unscaled atmospheric compensation spectra (transmittance and upwelling radiance) are extracted from the data. The step is carried out by application of a specially designed, line-fitting procedure to a scatter plot constructed from the hyperspectral data. The compensation spectra are defined in terms of the slope and intercept parameters of the line. In the second step, these unscaled compensation spectra are scaled to quantitative compensation spectra. EELM has been applied to airborne long wave infrared (LWIR; ~5.7 μm to ~11.7 μm) HSI data. The EELM derived ground-leaving radiance spectra generally contain fewer residual atmospheric spectral features and also this algorithm lead to a good atmospheric compensation. Therefore derive a good agreement between field and data spectra. The results show that a good agreement between field and data spectra emissivity for all kind of in-scene targets. The sensor that used in this work is Telops Hyper-Cam.

Thermal hyperspectral Target detection, Empirical Line Method, Emissivity, Atmospheric compensation, Radiance