Sonar-to-Satellite Translation using Deep Learning

Abstract

Sonar images pose hindrances when being elucidated for applications such as underwater navigation and localization. On the other hand, satellite images are simpler to be interpreted, but require GPS that is unavailable underwater due to absorption phenomena. Thus, we propose a neural network capable of translating an acoustic image acquired underwater to a textured image. We called the process sonar-to-satellite translation. We adopted a state-of-the-art neural architecture on a dataset comprised of sonar data and their respective satellite images. The experimental results show our method can extract interesting features from acoustic images and generate an informative texture image.