Estimation of noise parameters on sonar images

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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.

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