Clearing the Waters: A New Way to Fix Sun Glare in Drone Photos

There's a big problem that often happens when drones take pictures of water. The sun's reflection, called sun glint, can make it hard to see what's really going on in the water. This is especially true near the coast, where the water is often murky. Old ways of fixing this problem, using near-infrared light and other methods, often make mistakes. They can overcorrect in murky areas and mess up the visible light spectrum. It is important because scientists need accurate water quality data from drones to monitor the environment. Imagine you're trying to take a picture of something, but the sun is shining right into the camera. The picture is ruined. That's what happens when sun glint hits a drone's camera. It's a common issue, and it's a big problem for scientists who use drones to monitor water quality. The water near the coast is often dirty and full of particles, making it hard to get a clear picture. The old ways of fixing this problem, using near-infrared light and other methods, often make mistakes. They can overcorrect in murky areas and mess up the visible light spectrum.That's why a new method called SUGAR was created. SUGAR is an open-source tool that combines different approaches to fix the sun glint problem in drone photos. It uses principles from near-infrared and TV methods to correct the glint while keeping the rest of the picture clear. This new method has been tested in real-life situations, like flying drones over the coast of Singapore. The results were impressive. SUGAR reduced the glint-affected areas by 40-80% while keeping the non-glint areas clear. This means that scientists can now get more accurate data about water quality. The results were impressive. SUGAR reduced the glint-affected areas by 40-80% while keeping the non-glint areas clear. This means that scientists can now get more accurate data about water quality. The tests showed that SUGAR improved the accuracy of turbidity measurements, which is a key factor in water quality. The error rate was reduced from 0. 464 to 0. 183 FNU for multispectral imagery and from 0. 551 to 0. 285 FNU for hyperspectral imagery. This is a significant improvement, and it shows that SUGAR is a promising tool for monitoring water quality. This new method is a game-changer for scientists who use drones to monitor water quality. With SUGAR, they can get more accurate data and make better decisions about how to protect our coasts. The tool is open-source, which means anyone can use it and improve it. This is a big step forward in the fight to protect our environment.