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

机译:一种改进的方法,以防止在迭代频谱平滑温度发射率分离中出现虚假最小值

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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.
机译:在高光谱热红外遥感中,迭代光谱平滑温度/发射率分离(ISSTES)是目前同时检索地表温度(LST)和发射率(LSE)的最流行方法。但是,当噪声达到一定强度时,可能会导致严重的问题,这会导致ISSTES下降到错误的最小值,因此LST和LSE的误差远远超出了公差。在本文中,仿真数据和实测数据均用于显示问题如何发生,并提出了ISSTES-Extreme(ISSTES-E)方法来解决该问题。结果表明,当原始方法未能获得有效答案时,新方法能够防止错误的最小值。

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