Vehicle operations in underwater environments are frequently compromised by poor visibility conditions. In this thesis, we propose an end-to-end mosaicing framework tailored to the characteristics of forward-looking sonar imagery in order to build consistent overviews of planar underwater areas regardless of water visibility. Our solution targets versatility: it enables the generation of acoustic mosaics that involve roto-translational motions and comprise different vehicle tracklines, it is suitable for a wide range of scenarios, it can be applicable on data collected with minimally instrumented vehicles, and it allows both offline and real-time operation. To this end, we address the key problem of image registration on forward-looking sonar images and we provide solutions for the global alignment of the sonar frames along the trajectory as well as their blending into a smooth acoustic mosaic. To validate the full proposed framework, an extensive experimental section is reported showing successful results in relevant field applications.
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