University of Maryland researchers helped create an imaging technology that could one day result in video cameras able to peer through fog, smoke, driving rain, murky water, skin, bone and other materials that obscure objects from view by reflecting scattered light.
Computer science Assistant Professor Christopher Metzler and doctoral student Brandon Feng collaborated with Rice University Professor Ashok Veeraraghavan M.S. ’04, Ph.D. ’08 and Rice doctoral student Haiyun Guo to develop what they’re calling NeuWS (neural wavefront shaping). Described in a paper published recently in the journal Science Advances, it opens up new possibilities for enhanced visibility in challenging environments.
NeuWS is based on the concept that light waves possess two fundamental properties: magnitude and phase. Directly measuring phase, while crucial for overcoming scattering effects, is impractical due to the high-frequency nature of optical light. Instead, they utilize "wavefronts"—single measurements containing both phase and intensity information—and employ advanced computational processing to rapidly decipher the phase information from several hundred wavefront measurements per second.
By harnessing state-of-the-art spatial light modulators, which can capture multiple measurements per second, the researchers successfully demonstrated the capture of full-motion video of objects moving through media that scatter light.
In one set of experiments, a microscope slide containing a printed image of an owl or a turtle was spun on a spindle and filmed by an overhead camera. Light-scattering media like slides coated with nail polish, slices of chicken breast and light-diffusing films were placed between the camera and target slide.
In each case, the experiments showed NeuWS could produce clear video of the spinning figures, a capability that could one day be useful in medical imaging, safety and security applications, and underwater exploration.
This article was based on a news release from Rice University.
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