A modified method to prevent false minimums occurring in iterative spectrally smooth temperature emissivity separation

In hyperspectral thermal infrared remote sensing, iterative spectrally smooth temperature / emissivity separation (ISSTES) is currently the most popular method to retrieve land surface temperature (LST) and emissivities (LSEs) at the same time. However, a serious problem may occur when noise reaches certain intensities, which causes ISSTES to fall into a false minimum, and thus the errors of LST and LSEs are far beyond tolerance. In this paper, both simulated and measured data were used to show how the problem would occur, and the ISSTES-Extreme (ISSTES-E) method was proposed to fix the problem. The results reveal that the new method is able to prevent the false minimum when the original method fails to come to a valid answer.