How NASA uses fluid lensing to see through the ocean's distorting waves

Nature · Published 24 October 2026 Swipe more like this →

In short: The ocean covers over 70% of our planet, yet its surface acts like a broken lens. Waves magnify and shrink everything beneath them, making it nearly impossible to measure the true size or location of vital underwater ecosystems like Indonesia's Raja Ampat reefs.

For researchers, the primary obstacle to studying the ocean is refraction. As Ved Chirayath, a scientist at NASA’s Ames Research Center, explains, waves create a deceptive visual environment. When a wave crest passes over an object, it acts as a magnifying lens, making things appear larger; conversely, when a trough passes, objects appear smaller. Without a way to correct these distortions, scientists cannot accurately determine the size, extent, or movement of underwater features. This optical instability makes it incredibly difficult for scientists to gather reliable data about submerged objects.

To solve this, Chirayath developed FluidCam, a specialized camera mounted on Unmanned Aerial Vehicles (UAVs). The technology relies on a technique called fluid lensing and custom software designed to turn wave distortion into an advantage. Instead of merely correcting for the light's refraction, the software uses the waves' magnification effect to actually improve image resolution. This allows the system to capture terabytes of 3D imagery at a resolution of 0.5 cm. The process involves training supercomputers to recognize how various wave sizes impact the resulting imagery.

This precision is critical for monitoring the health of coral reefs, which face significant degradation from acidification, pollution, over-harvesting, and rising temperatures. By integrating data from airborne and satellite instruments, the technology can distinguish between coral and other materials with 95% greater accuracy than previous methods. Through the NeMO-Net observation and training network, scientists and the public can help classify these 3D maps, with the ultimate goal of deploying a space-based FluidCam to monitor global reef health from orbit. The NeMO-Net network provides a database for training these supercomputers to perform global classifications. Eventually, the team hopes to launch a FluidCam from orbit to map these ecosystems globally.

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