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19 August 2009 Noise and model uncertainties in ocean color remote sensing
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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.
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Robert Frouin and Bruno Pelletier "Noise and model uncertainties in ocean color remote sensing", Proc. SPIE 7459, Ocean Remote Sensing: Methods and Applications, 745905 (19 August 2009);

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