Mitigation o f Atmospheric Effects in Hyperspectral Data Analysis

摘要

For hyperspectral data analysis, the general objective for atmospheric compensation algorithms is to remove solar illumination and atmospheric effects from the measured spectral data so that surface reflectance can be retriceved. This then allows for comparison with library data for target identification. Recent aadvances in spectral sensing capability have led to the d evelopment of a number of atmospheric compensation algorithms for hyperectral data analysis. In this paper, three topics will be d iscussed: (1) algorithm evaluation of two physics-based approaches: ATREM and the AFRL model, (2) sensitivity analysis of the effects of varioous input parameters to surface reflectance retrieval, and (3) algorithm enhancements of how water vapor and aerosol retrievals can be better conducted than current algorithms.