Title :
Side-scan sonar simulation for a kernelized seafloor shape reconstruction approach
Author_Institution :
Fraunhofer Inst. of Optron., Syst. Technol. & Image Exploitation IOSB, Karlsruhe, Germany
Abstract :
In this paper we show how an existing pixel-based surface elevation estimation method for side-scan sonar data can be enhanced by using a kernelized surface representation. We discuss a Bayesian formulation for the side-scan imaging process and describe how methods of space carving and inverse ray tracing built on Markov Random Fields (MRF) can be introduced to the task of surface estimation from side-scan sonar data.
Keywords :
Bayes methods; Markov processes; geophysical image processing; image reconstruction; oceanographic techniques; ray tracing; seafloor phenomena; sonar; surface reconstruction; Bayesian formulation; MRF; Markov random fields; inverse ray tracing; kernelized seafloor shape reconstruction approach; kernelized surface representation; pixel-based surface elevation estimation method; side-scan imaging process; side-scan sonar data; side-scan sonar simulation; space carving; surface estimation; Estimation; Kernel; Mathematical model; Shape; Sonar measurements; Surface treatment;
Conference_Titel :
OCEANS - Bergen, 2013 MTS/IEEE
Conference_Location :
Bergen
Print_ISBN :
978-1-4799-0000-8
DOI :
10.1109/OCEANS-Bergen.2013.6607992
