  Shallow water and coastal aquatic ecosystems such as coral reefs and seagrass
meadows play a critical role in regulating and understanding Earth's changing
climate and biodiversity. They also play an important role in protecting towns
and cities from erosion and storm surges. Yet technology used for remote
sensing (drones, UAVs, satellites) cannot produce detailed images of these
ecosystems. Fluid lensing effects, the distortions caused by surface waves and
light on underwater objects, are what makes the remote sensing of these
ecosystems a very challenging task. Using machine learning, a proof of concept
model was developed that is able to remove most of these effects and produce a
clearer more stable image.
