Satellite and Underwater Sonar Image Matching Using Deep Learning
Matheus M. dos Santos, Giovanni G. De Giacomo, Paulo Drews, Sílvia Silva da Costa Botelho · 2019
Aerial images provide rich information about the Earth surface, while underwater perception is severely limited due to the physical characteristic of water. This work proposes a new problem domain where a matching process fuses aerial and underwater images. The proposal is designed to aid underwater navigation in partially structured environments such as marinas and harbors. A pipeline combining image processing techniques and Convolutional Neural Networks is presented. The method is validated in a real dataset with quantitative and qualitative results.