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The invasive species of brown algae <i>Sargassum</i> gathers in large aggregations in the Caribbean Sea, and has done so especially over the last decade. These aggregations wash up on shores and decompose, leading to many socio-economic issues for the population and the coastal ecosystem. Satellite ocean color data sensors such as Sentinel-3/OLCI can be used to detect the presence of <i>Sargassum</i> and estimate its fractional coverage and biomass. The derivation of <i>Sargassum</i> presence and abundance from satellite ocean color data first requires atmospheric correction; however, the atmospheric correction procedure that is commonly used for oceanic waters needs to be adapted when dealing with the occurrence of <i>Sargassum</i> because the non-zero water reflectance in the near infrared band induced by <i>Sargassum</i> optical signature could lead to <i>Sargassum</i> being wrongly identified as aerosols. In this study, this difficulty is overcome by interpolating aerosol and sunglint reflectance between nearby <i>Sargassum-</i>free pixels. The proposed method relies on the local homogeneity of the aerosol reflectance between <i>Sargassum</i> and <i>Sargassum</i>-free areas. The performance of the adapted atmospheric correction algorithm over <i>Sargassum</i> areas is evaluated. The proposed method is demonstrated to result in more plausible aerosol and sunglint reflectances. A reduction of between 75% and 88% of pixels showing a negative water reflectance above 600 nm were noticed after the correction of the several images.