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    This work describes some of the ongoing activities in the framework of the EU-sponsored project SITAR aimed at developing acoustic methods for imaging of waste barrels/containers of small dimension buried in unconsolidated sea sediments. In particular, the work relies on acoustic sub-bottom scattering measurement techniques, with adaptive geometrical configuration of the transmitting/receiving system. The approach ultimately leads to a full 3D measurement of the acoustic scattered field, including bottom and sub-bottom effects, plus the scattering due to buried objects in the scene. The 3D dense acoustic image is then processed in order to automatically extract relevant object(s) features, as size, 3D orientation, impedance contrast; this is obtained through a sequence of processing steps including filtering, enhancement, restoration and image segmentation. Preliminary results obtained with simulative data are presented: data are obtained by modeling the surfaces of both seabed and object(s) as a dense, random grid of discrete scatterers, following the Rayleigh reflection coefficient, and integrating the response of the scatterers. The effects due to absorption and refraction moving from water to sediments are also considered. Sediment volume inhomogeneities are modeled by a random distribution of small asymmetric scattering volumes, characterized by their 3D dimensions, density, and reflection coefficient. A volume growing segmentation approach has been applied, showing efficient segmentation capabilities, and robustness to uncertainty.


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