Deep seafloor characterization with multibeam echosounders by image segmentation using angular acoustic variations

Samantha Dugelay; Christine Graffigne; J. M. Augustin

doi:10.1117/12.253450

8 October 1996 Deep seafloor characterization with multibeam echosounders by image segmentation using angular acoustic variations

Samantha Dugelay, Christine Graffigne, J. M. Augustin

Author Affiliations +

Proceedings Volume 2823, Statistical and Stochastic Methods for Image Processing; (1996) https://doi.org/10.1117/12.253450
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

The new generation of low-frequency echosounders, primarily used for bathymetric purposes, are also able to record acoustic images of the sea floor. Reflected energy, as a function of the incidence angle, is known to be strongly dependent on seabed type, and therefore stands as a potential tool in sea floor characterization. On the other hand, acoustic images of the reflected energy, illustrate the variability of the acoustic interface and are invaluable for sea floor cartography. In this paper we describe a method of semi-automatic mosaic interpretation where the two different aspects are considered simultaneously. This is achieved by supervised segmentation using a Markov Random Field model where the neighborhood system and energies have been carefully studied in order to comply to a priori knowledge. We present results obtained with this method, enhancing the possibility of using such a technique for low- frequency echosounders.

Citation Download Citation

Samantha Dugelay, Christine Graffigne, and J. M. Augustin "Deep seafloor characterization with multibeam echosounders by image segmentation using angular acoustic variations", Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); https://doi.org/10.1117/12.253450

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