A physics-based unmixing method for thermal hyperspectral images

The estimation of surface emissivity and temperature from thermal hyperspectral data is a challenge. There are several methods that estimate the temperature and the emissivity by assuming that the pixel is composed by a single material. However, the estimation of the temperature on a mixed pixel, i.e. a pixel composed by more than one material, is more complex and has scarcely been investigated in the literature. This paper addresses this issue by jointly estimating the materials composing the mixed pixel and their temperatures. It uses an unmixing method based on the linearization of the Black Body law. The performance of this strategy is studied using synthetic data and a real thermal image acquired by the TASI sensor.