Seabed Classification From Multispectral Multibeam Data
نویسندگان
چکیده
Given the recent increase in availability of multispectral multibeam echosounder data, this work aims to identify suitable processing and classification methodologies for seabed based on such data. We propose a complete pipeline investigate adequacy state-of-the-art algorithms perform backscatter data alone, when additional sources are considered. Starting from raw acquisition we generate region-wide composite images through noise removal, inpainting/gap-filling mosaicking. Ground truth situ samples used. have tried different methods, including random forests, support vector machines, multilayer perceptrons, with latter providing best results. Quantitative qualitative evaluation five surveys indicate high performance only while features, like bathymetry, bathymetric positional index (BPI), or encoding, offer limited gains. web service further interest topic.
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ژورنال
عنوان ژورنال: IEEE Journal of Oceanic Engineering
سال: 2023
ISSN: ['1558-1691', '0364-9059', '2373-7786']
DOI: https://doi.org/10.1109/joe.2023.3267795