EVALUATION OF SCENE-BASED EMPIRICAL APPROACHES FOR ATMOSPHERIC CORRECTION OF HYPERSPECTRAL IMAGERY

摘要

The hyperspectral remotely sensed imagery is used in vast applications, especially in agriculture, mineralogy, geology, ecology and surveillance. Although it can give us abundant information with high spectral resolution, the presence of atmosphere with gases and aerosols alters the signal, leading to reduce and scatter the energy so that radiance does not interact with the ground surface. Therefore, if we demand reliable and accurate reflectance which is a property of ground feature, we have to carry out atmospheric correction for hyperspectral imagery. In this paper we evaluate scene-based empirical approaches that merely depend on statistics of image which can reduce the atmospheric effect without having any meteoric and geometric measurement. The results show that empirical line calibration is the most accurate method.