a grain of salt or a camera? researchers from princeton and washington universities develop an ultracompact camera that can produce crisp, full-color images on par with a conventional compound camera lens 500,000 times larger in volume. the system relies on a technology called a ‘metasurface’, studded with 1.6 million cylindrical posts. the device can be produced much like a computer chip!

‘we could turn individual surfaces into cameras that have ultra-high resolution, so you wouldn’t need three cameras on the back of your phone anymore, but the whole back of your phone would become one giant camera. we can think of completely different ways to build devices in the future,’ says felix heide, the study’s senior author and an assistant professor of computer science at princeton.

(above) the ultracompact camera relies on a technology called a metasurface, which is studded with 1.6 million cylindrical posts and can be produced much like a computer chip.

(banner)video sourced from princeton computational imaging lab

image courtesy of the researchers/source: university of princeton

micro-sized system have always had a great potential to spot anomalies in he human body as well as enable sensing for super-small robots, but pas approaches captured fuzzy, distorted images with limited fields of view. at last, authors at princeton university and the university of washington have overcome these obstacles. while a traditional camera uses a series of curved glass or plastic lenses to bend light rays into focus, the optical system relies on a technology called a metasurface. this, is made with a glass-like material that is compatible with standard manufacturing methods meaning that the design can be easily mass-produced at lower costs that conventional lenses.

side by side comparisons between the conventional (left) and the nano camera (right)

snippet from video/source: university of princeton computational imaging lab

just half a millimeter wide, each of the 1.6 million posts of the nano-sized device functions like an optical antenna. varying the design of each post is necessary to correctly shape the entire optical wavefront. with the help of machine learning-based algorithms, each posts’ interaction with light combine to produce the highest-quality images and widest field of view. 

because of the number of antennas and the complexity of their interactions with light, this type of simulation can use massive amounts of memory and time,’ explains co-lead author, shane colburn.

previous micro-sized cameras (left) captured fuzzy, distorted images with limited fields of view. a new system called neural nano-optics (right) can produce crisp, full-color images on par with a conventional compound camera lens.

image courtesy of the researchers/ source: university of princeton

‘although the approach to optical design is not new, this is the first system that uses a surface optical technology in the front end and neural-based processing in the back. the significance of the published work is completing the herculean task to jointly design the size, shape and location of the metasurface’s million features and the parameters of the post-detection processing to achieve the desired imaging performance,’ says joseph mait, a consultant at mait-optik and a former senior researcher and chief scientist at the U.S. army research laboratory.

comparison between neutral nano optics (left) and ground truth with compound optic (right)

felix heide, the study’s senior author, also envisions using ultracompact imagers to create surfaces as sensors. enabled by a joint design on the hardware and computational processing, the system could enable minimally invasive endoscopy with medical robots to diagnose and treat diseases, and improve imaging for other robots with size and weight constraints. 

‘it’s been a challenge to design and configure these little nano-structures to do what you want,’ says ethan tseng, a computer science ph.d. student at princeton who co-led the study. ‘for this specific task of capturing large field of view RGB images, it was previously unclear how to co-design the millions of nano-structures together with post-processing algorithms.’

existing state-of-the-art images (left two) compared to the nano-camera (second from right) and ground truth with compound optic (right)

research: university of princeton, university of washington

authors: felix heide, ethan yseng, arka majumdar, shane colburn, joseph mait, luocheng huang, james whitehead

supported by: national science foundation, the U.S. department of defense, the UW reality lab, facebook, google, futurewei technologies, amazon

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