Automated Generation of Geo-Referenced Mosaics From Video Data Collected by Deep-Submergence Vehicles: Preliminary Results

Many advances in understanding geologic, tectonic, biologic, and sedimentologic processes in the deep ocean are facilitated by direct observation of the seafloor. However, making such observations is both difficult and expensive. Optical systems (e.g., video, still camera, or direct observation) will always be constrained by the severe attenuation of light in the deep ocean, limiting the field of view to distances that are typically less than 10 meters. Acoustic systems can 'see' much larger areas, but at the cost of spatial resolution. Ultimately, scientists want to study and observe deep-sea processes in the same way we do land-based phenomena so that the spatial distribution and juxtaposition of processes and features can be resolved. We have begun development of algorithms that will, in near real-time, generate mosaics from video collected by deep-submergence vehicles. Mosaics consist of >>10 video frames and can cover 100's of square-meters. This work builds on a publicly available still and video mosaicking software package developed by Rzhanov and Mayer. Here we present the results of initial tests of data collection methodologies (e.g., transects across the seafloor and panoramas across features of interest), algorithm application, and GIS integration conducted during a recent cruise to the Eastern Galapagos Spreading Center (0 deg N, 86 deg W). We have developed a GIS database for the region that will act as a means to access and display mosaics within a geospatially-referenced framework. We have constructed numerous mosaics using both video and still imagery and assessed the quality of the mosaics (including registration errors) under different lighting conditions and with different navigation procedures. We have begun to develop algorithms for efficient and timely mosaicking of collected video as well as integration with navigation data for georeferencing the mosaics. Initial results indicate that operators must be properly versed in the control of the video systems as well as maintaining vehicle attitude and altitude in order to achieve the best results possible.