Researchers used infrared images to recreate a near-perfect photo in visible light.
The monochromatic black-and-green that defined night vision for decades is quickly receding into the past. , and researchers across the world are racing to develop even more advanced ways of seeing in the dark. A new proof-of-principle study offers intriguing hints about how the next generation of such technology might work., researchers demonstrate that a deep learning algorithm can build a full-color reconstruction of a scene using only infrared images the human eye can't see.
. The light waves we can see range from roughly 400 nanometers to roughly 700 nanometers . If someone were in a room with no windows and a bright bulb casting light at a wavelength of 800 nanometers, they would experience total darkness. A mosquito or a pit viper, on the other hand, could see just fine. A human could also see a version of the scene if they were looking through an infrared camera. That's because it's not a technical challenge to take photos in infrared light. The challenge is rendering those images in visible light so a human viewer can make sense of what they're seeing. For example, thermal imaging uses a technique called pseudocolor to make an infrared image visible.
We probably won't see this technology in night-vision goggles anytime soon, but this proof-of-concept shows that full-color night vision is on the horizon. Stay ahead with the latest science, technology and innovation news, for free:
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