A team of researchers from Intel and the University of Illinois at Urbana-Champaign recently developed a neural network that performs incredible post-processing enhancements on extreme low-light photographs. The AI takes images which appear pitch black or full of noise and makes them look bright, clean, and colorful.
How it’s done: The researchers created the See-in-the-Dark (SID) data set, a group of 5,094 short-exposure images in RAW format, and fed it to a deep learning system. They then trained the AI to compare the information contained in the low-light images to corresponding photographs taken at longer exposure. The results are pretty amazing:
Why it matters: Real-time extreme low-light image processing could become a reality. Photographers can already take pretty good extreme low-light images, but it requires a tripod and long exposure times. Current camera technology is impractical for extreme low-light photography in all but optimum conditions, and entirely unsuited for devices like night-vision goggles.
But with further development this AI could, theoretically, be optimized to provide real-time image processing capable of augmenting any camera or optics system. If we toss in some Army AI, it’s easy to imagine the development of a headset device designed to allow humans to see perfectly in the dark and perform facial recognition through walls.
The Next Web’s 2018 conference is almost here, and it’ll be 💥💥. Find out all about our tracks here.