Along with flying and invisibility, high on the list of every child's aspirational superpowers is the ability to see through or around walls or other visual obstacles. That capability is now a big step closer to reality as scientists from the University of Wisconsin-Madison and the Universidad de Zaragoza in Spain, drawing on the lessons of classical optics, have shown that it is possible to image complex hidden scenes using a projected "virtual camera" to see around barriers.

Once perfected, the technology could be used in a wide range of applications, from defense and disaster relief to manufacturing and medical imaging. The work has been funded largely by the military through the U.S. Defense Department's Advanced Research Projects Agency (DARPA) and by NASA, which envisions the technology as a potential way to peer inside hidden caves on the moon and Mars.

Technologies to achieve what scientists call "non-line-of-sight imaging" have been in development for years, but technical challenges have limited them to fuzzy pictures of simple scenes. Challenges that could be overcome by the new approach include imaging far more complex hidden scenes, seeing around multiple corners, and taking video.

"This non-line-of sight imaging has been around for a while," says Andreas Velten, a professor of biostatistics and medical informatics in the UW School of Medicine and Public Health and the senior author of the new study. "There have been a lot of different approaches to it."

The basic idea of non-line-of-sight imaging, Velten says, revolves around the use of indirect, reflected light, a light echo of sorts, to capture images of a hidden scene. Photons from thousands of pulses of laser light are reflected off a wall or another surface to an obscured scene and the reflected, diffused light bounces back to sensors connected to a camera. The recaptured light particles or photons are then used to digitally reconstruct the hidden scene in three dimensions.

"We send light pulses to a surface and see the light coming back, and from that we can see what's in the hidden scene," Velten explains.

Recent work by other research groups has focused on improving the quality of scene regeneration under controlled conditions using small scenes with single objects. The work presented in the new report goes beyond simple scenes and addresses the primary limitations to existing non-line-of-sight imaging technology, including varying material qualities of the walls and surfaces of the hidden objects, large variations in brightness of different hidden objects, complex inter-reflection of light between objects in a hidden scene, and the massive amounts of noisy data used to reconstruct larger scenes.

Together, those challenges have stymied practical applications of emerging non-line-of-sight imaging systems. Velten and his colleagues, including Diego Gutierrez of the Universidad de Zaragoza, turned the problem around, looking at it through a more conventional prism by applying the same math used to interpret images taken with conventional line-of-sight imaging systems. The new method surmounts the use of a single reconstruction algorithm and describes a new class of imaging algorithms that share unique advantages.