Estimation of noise parameters on sonar images

Francoise Schmitt; Max Mignotte; Christophe Collet; Pierre Thourel

doi:10.1117/12.253436

8 October 1996 Estimation of noise parameters on sonar images

Francoise Schmitt, Max Mignotte, Christophe Collet, Pierre Thourel

Proceedings Volume 2823, Statistical and Stochastic Methods for Image Processing; (1996) https://doi.org/10.1117/12.253436
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

We use the Markov random field model in order to segment sonar images, i.e. to localize the sea bottom areas and the projected shadow areas corresponding to objects lying on sea floor. This model requires on one hand knowledge about the statistical distributions relative to the different zones and ont the other hand the estimation of the law parameters. The Kolmogorov criterion or the (chi) ² criterion allow to estimate the distribution laws. The estimation maximization algorithm or the stochastic estimation maximization algorithm are used to determine the maximum likelihood estimate of the law parameters. Those algorithms are initialized with the Kmean algorithm. Results are showing on real sonar pictures.

Citation Download Citation

Francoise Schmitt, Max Mignotte, Christophe Collet, and Pierre Thourel "Estimation of noise parameters on sonar images", Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); https://doi.org/10.1117/12.253436

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