Hierarchical MRF modeling for sonar picture segmentation
This paper deals with sonar image segmentation based on a hierarchical Markovian modeling. The designed Markov random field (MRF) model takes into account both the phenomenon of speckle noise through Rayleigh's law, and notions of geometry related to the shape of object shadows. We adopt an 8-connexity neighbourhood in order to discriminate geometric and non-regular shadows. MRF are well adapted for this kind of segmentation where a priori knowledge about the shapes we are searching is available. Besides, the introduced hierarchical modeling allows us to successfully improve the sonar image segmentation while speeding up the iterative optimization scheme.