Paper
12 October 2006 Improved reflectance retrieval from hyper- and multispectral imagery without prior scene or sensor information
L. S. Bernstein, S. M. Adler-Golden, R. L. Sundberg, A. J. Ratkowski
Author Affiliations +
Abstract
We describe improvements to a recently developed VNIR-SWIR atmospheric correction method for hyper- and multispectral imagery, dubbed QUAC (QUick Atmospheric Correction). It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The newest implementation of QUAC is based on the assumption that the average reflectance of a collection of diverse material spectra, such as the endmember spectra in a scene, is effectively scene independent. This enables the retrieval of reasonably accurate reflectance spectra even when the sensor does not have a proper radiometric or wavelength calibration, or when the solar illumination intensity is unknown. The computational speed of the atmospheric correction method is significantly faster than for the first-principles methods, making it potentially suitable for real-time applications on aircraft and spacecraft. QUAC is applied to a diverse collection of hyper- and multispectral data sets and the results are compared to those obtained with the physics-based atmospheric correction code FLAASH (Fast Line of sight Atmospheric Analysis of Spectral Hypercubes).
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. S. Bernstein, S. M. Adler-Golden, R. L. Sundberg, and A. J. Ratkowski "Improved reflectance retrieval from hyper- and multispectral imagery without prior scene or sensor information", Proc. SPIE 6362, Remote Sensing of Clouds and the Atmosphere XI, 63622P (12 October 2006); https://doi.org/10.1117/12.705038
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Cited by 22 scholarly publications and 3 patents.
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KEYWORDS
Reflectivity

Sensors

Atmospheric corrections

Vegetation

Multispectral imaging

Calibration

Algorithm development

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