Researchers Develop Method to Dramatically Reduce Imaging Noise

Researchers at Stevens Institute of Technology created a 3D imaging system that uses light’s quantum properties to create images 40,000 times crisper than current technologies. The research could allow for better lidar sensing and detection, satellite mapping systems, deep-space communications, and medical imaging of the human retina.

Even with a mesh screen covering an object (top), the Stevens quantum 3D imaging technique generates images 40,000 times clearer (middle) than current technologies (bottom). Courtesy of Stevens Institute of Technology.

The technology is the first real-world demonstration of single-photon noise reduction using a method called quantum parametric mode sorting, or QPMS, which was first proposed by Yuping Huang, director of the Center for Quantum Science and Engineering at Stevens, and his team in a 2017 Nature paper. Unlike most noise-filtering tools that rely on a software-based post-processing to clean up noisy images, QPMS checks light’s quantum signatures through exotic nonlinear optics to create an exponentially cleaner image at the level of the sensor itself.

The work addresses a decades-old problem with lidar. Although light detectors used in these systems are sensitive enough to create detailed images from just a few photons, it’s difficult to differentiate reflected fragments of laser light from brighter background light such as sunbeams.

“The more sensitive our sensors get, the more sensitive they become to background noise,” Huang said. “That’s the problem we’re now trying to solve.”

The imaging system Huang and his team developed is able to differentiate returning photons from unwanted noisy photons from ambient light sources, which allows it to yield sharp 3D images, even when every signal-carrying photon is drowned out by 34 times as many noisy photons.

“By cleaning up initial photon detection, we’re pushing the limits of accurate 3D imaging in a noisy environment,” said Patrick Rehain, a Stevens doctoral candidate and the study’s lead author. “We’ve shown that we can reduce the amount of noise about 40,000 times better than the top current imaging technologies.”

That hardware-based approach could facilitate the use of lidar in noisy settings where computationally intensive post-processing isn’t possible. The technology could also be combined with software-based noise reduction to yield even better results.

“We aren’t trying to compete with computational approaches — we’re giving them new platforms to work in,” Rehain said.

QPMS noise reduction could allow lidar to be used to generate accurate, detailed 3D images at ranges of up to 30 kilometers. It could also be used for deep-space communication, where the sun’s harsh glare would ordinarily drown out distant laser pulses.

By enabling virtually noise-free single-photon imaging, the Stevens imaging system will help researchers create crisp, highly detailed images of the human retina using almost invisibly faint laser beams that won’t damage the eye’s sensitive tissues.

“The single-photon imaging field is booming,” Huang said. “But it’s been a long time since we’ve seen such a big step forward in noise reduction and the benefits it could impart to so many technologies.”