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Title: An expectation-maximization framework for the estimation of bathymetry from side-scan sonar images
Author: Coiras, E, Petillot, Y, Lane, DM
Year: 2005
Book / Journal: Oceans 2005 - Europe, Vols 1 and 2
Pages: 261-264
Abstract: In this paper a new procedure for the computation of seabed altitude information from side-scan sonar data is presented. Although side-scan sensors do not provide direct measures of seabed elevation, their images are directly related to seabed topography. Using a mathematical model for the sonar ensonification process, approximations to the seabed characteristics can be inferred from the sonar image. The problem is however severely under-constrained, in the sense that not all the parameters involved in the image formation process can be directly determined from the side-scan image. To overcome this difficulty, we propose the utilization of a multi-resolution expectation-maximization framework to select the most probable parameters from the solution space. At every iteration the estimated- solution is used to simulate a side-scan image of the observed scene, which is then be compared to the side-scan image actually observed; solution parameters are then refined using gradient-descent optimization. The process is repeated until convergence is achieved.
Keywords: ,
BibTex: @inproceedings{ ISI:000231762600049,
Author = {Coiras, E and Petillot, Y and Lane, DM},
Book-Group-Author = {{IEEE}},
Title = {{An expectation-maximization framework for the estimation of bathymetry
   from side-scan sonar images}},
Booktitle = {{Oceans 2005 - Europe, Vols 1 and 2}},
Year = {{2005}},
Pages = {{261-264}},
Note = {{Oceans 2005 Europe International Conference, Brest, FRANCE, JUN 20-23,
   2005}},
Abstract = {{In this paper a new procedure for the computation of seabed altitude
   information from side-scan sonar data is presented. Although side-scan
   sensors do not provide direct measures of seabed elevation, their
   images are directly related to seabed topography. Using a mathematical
   model for the sonar ensonification process, approximations to the
   seabed characteristics can be inferred from the sonar image. The
   problem is however severely under-constrained, in the sense that not
   all the parameters involved in the image formation process can be
   directly determined from the side-scan image. To overcome this
   difficulty, we propose the utilization of a multi-resolution
   expectation-maximization framework to select the most probable
   parameters from the solution space. At every iteration the estimated-
   solution is used to simulate a side-scan image of the observed scene,
   which is then be compared to the side-scan image actually observed;
   solution parameters are then refined using gradient-descent
   optimization. The process is repeated until convergence is achieved.}},
ISBN = {{0-7803-9103-9}},
Unique-ID = {{ISI:000231762600049}},
PDF: Coiras-OceansEurope2005.pdf

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