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Driving through fog can be tricky even for the best human driver. But a new camera could help vehicles navigate through tough weather on their own.

Built for just $500, the camera uses that strobe at nanosecond periods. It relies on time-of-flight photography, which measures how fast a light signal is reflected back to a camera to determine the distance of an object, a bit like a bat surveying a cave with sonar.

Developed by a team led by Ramesh Raskar of at MIT鈥檚 Media Lab, the 3D 鈥渘ano-camera鈥� uses a wave of strobing light to sweep across a scene, and then its software differentiates between light reflected off opaque surfaces and light moving through things like rain or glass.

Conventional motion sensors assume that one path of light is feeding the camera. A device like that would have trouble rendering, for example, both a window and the image behind it. With the nano-camera, light that reflects both off an object behind a window and on the glass itself is taken into account.

Unequal paths

The camera distinguishes between direct and scattered or diffracted light, so it could be used in vehicle collision-avoidance technology or medical imaging. Rain, fog and body tissue all send light scattering, but because the camera can accurately render the depth of translucent materials, it could give a clearer view of tissue structure or help distinguish a car鈥檚 bumper from within a blizzard.

鈥淣ot all optical paths are created equal,鈥� says , a computer vision researcher at the MIT Media Lab. To select which paths of light contribute to a pixel and eliminate the smearing that can happen when several rays of light converge, the team programmed the camera to pick out only a few of the finite number of photons acting on a pixel at one time.

鈥淥ur camera exploits the mathematical concept of sparsity, where we rely only on a few dominant optical paths,鈥� says signal-processing researcher Ayush Bhandari. 鈥淥ur algorithms selectively choose the light that acts on a pixel to more clearly render a 3D image.鈥�

Compared to previous work in the field of computational photography, this camera 鈥渢akes a clever and different approach鈥�, says Steve Marschner, who studies computer graphics and computational photography at Cornell University in Ithaca, New York. 鈥淭his is an exciting technology with a lot of potential that I expect will find application in surprising areas in the future.鈥�