Solving a “Holy Grail” Optical Imaging Problem – Scientists Develop Neural Wavefront Shaping Camera

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Engineers from Rice and Maryland have overcome the challenge of 'light scattering' with full-motion video. Engineers at Rice University and the University of Maryland have developed a full-motion video technology that could potentially be used to make cameras that peer through fog, smoke, driving r

have developed a full-motion video technology that could potentially be used to make cameras that peer through fog, smoke, driving rain, murky water, skin, bone, and other media that reflect scattered light and obscure objects from view.

“If you ask people who are working on autonomous driving vehicles about the biggest challenges they face, they’ll say, ‘Bad weather. We can’t do good imaging in bad weather.’” Veeraraghavan said. “They are saying ‘bad weather,’ but what they mean, in technical terms, is light scattering. If you ask biologists about the biggest challenges in microscopy, they’ll say, ‘We can’t image deep tissue in vivo.

So they instead measure incoming light as “wavefronts” — single measurements that contain both phase and intensity information — and use backend processing to rapidly decipher phase information from several hundred wavefront measurements per second. Metzler used the analogy of looking at the North Star at night through a haze of clouds. “If I know what the North Star is supposed to look like, and I can tell it is blurred in a particular way, then that tells me how everything else will be blurred.”

 

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