Seeing Around the Corner With Lasers—and Speckle

A new way to reconstruct images from interference patterns may one day help soldiers, rescue workers, and even self-driving cars

2 min read
Researchers used deep learning to create a new laser-based system that can image around corners in real time.
I spy trouble: Researchers used deep learning to create a new laser-based system that can image around corners in real time.
Illustration: Felix Heide/Princeton University

Researchers from Rice, Stanford, Princeton, and Southern Methodist University have developed a new way to use lasers to see around corners that beats the previous technique on resolution and scanning speed. The findings appear today in the journal Optica.

The U.S. military—which funded the work through DARPA grants—is interested for obvious reasons, and NASA wants to use it to image caves, perhaps doing so from orbit. The technique might one day also let rescue workers peer into earthquake-damaged buildings and help self-driving cars navigate tricky intersections.

One day. Right now it’s a science project, and any application is years away. 

The original way of corner peeping, dating to 2012, studies the time it takes laser light to go to a reflective surface, onward to an object and back again. Such time-of-flight measurement requires hours of scanning time to produce a resolution measured in centimeters. Other methods have since been developed that look at reflected light in an image to infer missing parts.

figures Penny for your thoughts: From the left: A letter on a penny-size disc, laser speckle encoding that letter, an initial computer reconstruction of the image, and the final reconstruction. Images: Stanford University/Optica

The latest method looks instead at speckle, a shimmering interference pattern that in many laser applications is a bug; here it is a feature because it contains a trove of spatial information. To get the image hidden in the speckle—a process called non-line-of-sight correlography—involves a bear of a calculation. The researchers used deep-learning methods to accelerate the analysis. 

“Image acquisition takes a quarter of a second, and we’re getting sub-millimeter resolution,” says Chris Metzler, the leader of the project, who is a post-doc in electrical engineering at Stanford. He did most of the work while completing a doctorate at Rice.

The problem is that the system can achieve these results only by greatly narrowing the field of view.

“Speckle encodes interference information, and as the area gets larger, the resolution gets worse,” says Ashok Veeraraghavan, an associate professor of electrical engineering and computer science at Rice. “It’s not ideal to image a room; it’s ideal to image an ID badge.”

The two methods are complementary: Time-of-flight gets you the room, the guy standing in that room, and maybe a hint of a badge. Speckle analysis reads the badge. Doing all that would require separate systems operating two lasers at different wavelengths, to avoid interference.

diagram of the in lab system Pinball wizard: The round-the-bend experiment took place in close quarters; researchers hope to scale it up Image: Southern Methodist University

Today corner peeping by any method is still “lab bound,” says Veeraraghavan, largely because of interference from ambient light and other problems. To get the results that are being released today, the researchers had to work from just one meter away, under ideal lighting conditions. A possible way forward may be to try lasers that emit in the infrared.

Another intriguing possibility is to wait until the wireless world’s progress to ever-shorter wavelengths finally hits the millimeter band, which is small enough to resolve most identifying details. Cars and people, for instance.

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