Researchers at Caltech and their colleagues have described a new method that essentially transforms nearby surfaces into lenses that can be used to indirectly image previously obscured objects. The technology is a form of non-line-of-sight (NLOS) sensing — or sensing that detects an object of interest outside of the viewer’s line of sight.
The new method – dubbed UNCOVER – does this by using nearby flat surfaces, such as walls, like a lens to clearly view the hidden object. Most current NLOS imaging technology will detect light from a hidden object that is passively reflected by a surface such as a wall, however, because surfaces such as walls predominantly scatter light, the techniques do not produce clear images.
While computational imaging methods can be used to extract information from the scattered light and improve the image clarity, they cannot generate high-resolution images. UNCOVER, however, directly counteracts scattering through its use of wavefront shaping technology – a technology that was previously unviable because it requires the use of a guidestar, an approximate point source of light that allows details of the hidden object to be deduced.
“We know that lenses image a point onto another point,” says electrical engineering graduate student Ruizhi Cao, the first author of a paper on the research. “If you are looking through a bad ‘lens’ with matte surfaces, the image of a point is now blurred, and the light spreads all over the place, but you can grind and polish the matte surface to navigate the light to the correct position. That is how a guidestar helps you in principle: It tells us where the tiny bumps are, so that we know how to correctly polish the surface.”
The researchers found that the hidden object itself could be used as the guidestar. The result is an NLOS imaging method that pieces the scattered light back together into a clear image of the hidden object.
The imaging method, say the researchers, might be useful for autonomous driving, as well as rescue missions and other remote-sensing related missions.
“We can see all the traffic on the crossroads with this method,” says Cao, “his might help the cars to foresee the potential danger that one is not able to see directly.”
The use of UNCOVER might allow automobiles to see as well as humans, say the researchers, but also for humans to become better drivers. Whereas a human driver might be able to spot an upcoming jaywalker a few feet away, an autonomous car outfitted with UNCOVER technology could potentially be able to spot such an instance on the next block, provided that the imaging conditions are optimal.
UNCOVER imaging could also prove useful beyond Earth – for example, in future robotic missions to explore Mars, say the researchers.
“We are counting on the rovers to take images of another planet to help us develop a better understanding about that planet,” says Cao. “However, for those rovers, some places might be hard to reach because of limited resources and power. With the non-line-of-sight imaging technique, we don’t need the rover itself to do that. What is needed is to find a place where the light can reach.”
For more, see “High-resolution non-line-of-sight imaging employing active focusing.”