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Proceedings Paper

Noise and model uncertainties in ocean color remote sensing
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Paper Abstract

The performance of ocean color inversion algorithms is strongly impacted by the various sources of uncertainties, including measurement noise, calibration noise, pre-processing and radiation transfer modeling uncertainties. In this work, an attempt at assessing the overall departure of theory from measurements is conducted based on an in-situ matchup data set. The statistical properties of these differences are first estimated, and are next used to define a Bayesian solution to the inverse problem of atmospheric correction. It is found that there may exist multiple solutions to the inverse problem. The methodology also allows the construction of general confidence domains on the retrieved marine reflectance, without shape restrictions.

Paper Details

Date Published: 19 August 2009
PDF: 11 pages
Proc. SPIE 7459, Ocean Remote Sensing: Methods and Applications, 745905 (19 August 2009); doi: 10.1117/12.829794
Show Author Affiliations
Robert Frouin, Univ. of California, San Diego (United States)
Bruno Pelletier, CNRS, Univ. Montpellier II (France)

Published in SPIE Proceedings Vol. 7459:
Ocean Remote Sensing: Methods and Applications
Robert J. Frouin, Editor(s)

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