Match Elimination using Cycle Basis in Underwater Optical Mapping

The use of image mosaicing methods for underwater optical mapping has become very popular owing to the rapid progress in obtaining optical data using robotic platforms. In order to obtain globally consistent mosaics, one of the essential steps is global alignment for finding best image registration parameters, which employs non-linear optimisation methods to minimise the error metric defined over correspondences detected between overlapping image pairs. In this paper, we propose a method that uses graph theory principles to reduce the total number of overlapping image pairs used in the global alignment process without degrading the final mosaic quality. This reduction allows for obtaining image mosaics with reduced computational cost and time. The method is validated through two experiments that involve challenging underwater datasets.