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Technical Program

Paper Detail

Paper:	IMDSP-P14.7
Session:	Image Formation
Time:	Friday, May 19, 10:00 - 12:00
Presentation:	Poster
Topic:	Image and Multidimensional Signal Processing: Geophysical and Seismic Imaging
Title:	Unsupervised calibrated sonar imaging for seabed observation using hidden Markov Random fields
Authors:	Ronan Fablet, Ifremer/STH/LASAA, France; Jean-Marie Augustin, Ifremer/TSI/AS, France
Abstract:	This paper deals with seabed imaging issued from sonar systems. Such imaging systems produce images of back-scattering (BS) strength relative to physical seabed characteristics. However, these BS measurements are not only seabed-related but also dependent on the incident angle. Therefore, to enhance the quality of such seabed imaging systems, we develop an unsupervised approach to compensate for these seabed-related angular dependencies. Our approach combines robust estimation and hidden Markov random fields. Results on real data demonstrate the relevance of our approach to improve seabed observation.