Paper
23 August 2000 Mitigation of atmospheric effects in hyperspectral data analysis
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Abstract
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 retrieved. This then allows for comparison with library data for target identification. Recent advances in spectral sensing capability have led to the development of a number of atmospheric compensation algorithms for hyperspectral data analysis. In this paper, three topics will be discussed: (1) algorithm evaluation of two physics-based approaches: ATREM and the AFRL model, (2) sensitivity analysis of the effects of various input parameters to surface reflectance retrieval, and (3) algorithm enhancements of how water vapor and aerosol retrievals can be better conducted than current algorithms. Examples using existing hyperspectral data, including those from HYDICE, AVIRIS will be discussed. Results will also be compared with truth information derived from ground and satellite based meteorological data.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hsiao-hua K. Burke, Michael K. Griffin, and J. William Snow "Mitigation of atmospheric effects in hyperspectral data analysis", Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); https://doi.org/10.1117/12.410367
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Cited by 2 scholarly publications.
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KEYWORDS
Atmospheric modeling

Aerosols

Atmospheric particles

Reflectivity

Absorption

Atmospheric physics

Visibility

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