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Open AccessArticle

A General Approach to Enhance Short Wave Satellite Imagery by Removing Background Atmospheric Effects

Swedish Meteorological and Hydrological Institute (SMHI), SE-60176 Norrköping, Sweden
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Remote Sens. 2018, 10(4), 560; https://doi.org/10.3390/rs10040560
Received: 2 February 2018 / Revised: 23 March 2018 / Accepted: 26 March 2018 / Published: 5 April 2018
(This article belongs to the Special Issue Atmospheric Correction of Remote Sensing Data)
Atmospheric interaction distorts the surface signal received by a space-borne instrument. Images derived from visible channels appear often too bright and with reduced contrast. This hampers the use of RGB imagery otherwise useful in ocean color applications and in forecasting or operational disaster monitoring, for example forest fires. In order to correct for the dominant source of atmospheric noise, a simple, fast and flexible algorithm has been developed. The algorithm is implemented in Python and freely available in PySpectral which is part of the PyTroll family of open source packages, allowing easy access to powerful real-time image-processing tools. Pre-calculated look-up tables of top of atmosphere reflectance are derived by off-line calculations with RTM DISORT as part of the LibRadtran package. The approach is independent of platform and sensor bands, and allows it to be applied to any band in the visible spectral range. Due to the use of standard atmospheric profiles and standard aerosol loads, it is possible just to reduce the background disturbance. Thus signals from excess aerosols become more discernible. Examples of uncorrected and corrected satellite images demonstrate that this flexible real-time algorithm is a useful tool for atmospheric correction. View Full-Text
Keywords: atmospheric correction; pytroll; satellite remote sensing; surface reflectance; rgb images; ocean color atmospheric correction; pytroll; satellite remote sensing; surface reflectance; rgb images; ocean color
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Scheirer, R.; Dybbroe, A.; Raspaud, M. A General Approach to Enhance Short Wave Satellite Imagery by Removing Background Atmospheric Effects. Remote Sens. 2018, 10, 560.

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