论文标题
从空间图像中去除流体镜头效应
Removing fluid lensing effects from spatial images
论文作者
论文摘要
浅水和沿海水生生态系统（例如珊瑚礁和海草草地）在调节和了解地球不断变化的气候和生物多样性方面起着至关重要的作用。它们在保护城镇免受侵蚀和暴风雨的侵害方面也发挥了重要作用。然而，用于遥感的技术（无人机，无人机，卫星）无法产生这些生态系统的详细图像。流体镜头效应，表面波和水下物体上的光引起的扭曲，使这些生态系统的遥感成为非常具有挑战性的任务。使用机器学习，开发了概念模型的证明，能够消除大多数这些效果并产生更清晰的图像。
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.
