Researchers at the University of California Irvine are developing an AI-powered night vision camera that is capable of shooting full color images in complete darkness. Put simply, humans are able to see light in the visible spectrum (400-700 nm), and although some night vision systems use infrared light that is not perceptible to humans, their images rendered are transposed to a digital display presenting a monochromatic image in the visible spectrum.
So, the researchers developed an imaging algorithm powered by optimized deep learning architectures whereby infrared spectral illumination of a scene could be used to predict a visible spectrum rendering of the scene as if it were being viewed by a human withing the visible light spectrum. This means that it would be possible to digitally render a visible spectrum scene to humans when they are otherwise in complete “darkness” and only illuminated with infrared light.
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To achieve this goal, we used a monochromatic camera sensitive to visible and near infrared light to acquire an image dataset of printed images of faces under multispectral illumination spanning standard visible red (604 nm), green (529 nm) and blue (447 nm) as well as infrared wavelengths (718, 777, and 807 nm). We then optimized a convolutional neural network with a U-Net-like architecture to predict visible spectrum images from only near-infrared images,” said the researchers.
