Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data - Publikacja - MOST Wiedzy

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Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data

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The paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation of several statistical methods applied for analysis of a set of seafloor descriptors derived from multibeam data. In the paper, the use of Principal Component Analysis (PCA), as well as Canonical Discriminant Analysis (CDA) for reduction of the seafloor parameter space dimension is presented along with the obtained results. In addition, the use of the open source World Wind Java SDK tool for implementation of imaging and mapping of seafloor multibeam data, integrated with other elements of a scene and overlaid on rich background data, is also shown.

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Kategoria:
Publikacja w czasopiśmie
Typ:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Opublikowano w:
HYDROACOUSTICS nr 15, strony 123 - 130,
ISSN: 1642-1817
Język:
angielski
Rok wydania:
2012
Opis bibliograficzny:
Łubniewski Z., Stepnowski A.: Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data// HYDROACOUSTICS. -Vol. 15., (2012), s.123-130
Weryfikacja:
Politechnika Gdańska

wyświetlono 52 razy

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