Ultracompact Camera Is The Size Of A Salt Grain

By: April Carson



Researchers in the United States have developed a new imaging device with a diameter of just 500 nanometers (0.5 millimetres). The technology can produce clear, full-color pictures comparable to those produced using big compound camera lenses that are 500,000 times bigger in volume.


Micro-sized cameras have enormous potential to detect ailments in the human body and enable sensing for super-tiny robots, but previous methods produced only fuzzy, distorted images with restricted fields of view.


Until recently, scientists at the University of Washington and Princeton University had overcome these roadblocks with an ultracompact camera that is the size of a table salt. The space-saving design is also more energy efficient and can create sharp, full-color pictures equivalent to a standard compound camera lens 500 million times larger in volume. A research documenting the invention was published today in Nature Communications.


The technology may also be used to overcome limitations in size and weight while enabling minimally invasive endoscopy with medical robots to identify and treat illnesses, as well as allow other robots with size and weight restrictions to see more clearly. A single camera could, in principle, detect a full room. Thousands of these cameras might be placed together to provide whole-scene monitoring, turning surfaces into cameras.


The new optical system here, unlike traditional cameras that use a series of curved glass or plastic lenses to bend light rays into focus, uses technology called a metasurface, which can be manufactured similarly to a computer chip. Its surface is studded with 1.6 million cylindrical "nanoposts" – each roughly the size of the human immunodeficiency virus (HIV) – measuring just half a millimetre in diameter.


The geometry of each nanopost is unique, and it acts like an optical antenna. The entire optical wavefront must be properly formed by varying the design of each nanopost. The posts' interactions with light create both the best-quality pictures and the broadest field of view for a full-color metasurface camera to date, thanks to machine learning-based algorithms.



The camera's internal design, with its integrated optics and signal-processing techniques - two key elements in the camera's invention - helped to improve performance in natural light. In contrast, previous metasurface cameras were only able to produce high-quality images in laboratories or other ideal settings, according to Felix Heide, the study's senior author and Assistant Professor of Computer Science at Princeton.


Traditional metasurface technology has also been plagued with severe image distortions, small fields of view, and limited ability to capture the full spectrum of visible light. RGB imaging is a term that refers to the process of combining red, green, and blue light in order to generate different colors.


"The small microstructures we designed and configured to do what you want have been a challenge," said Ethan Tseng, a computer science PhD student at Princeton who co-leaded the research. "For this specific goal of capturing big field of view RGB photographs, it was previously unclear how to work with post-processing algorithms to co-design the millions of nano-structures."


This problem was addressed by Shane Colburn and his team, who developed a computational model to accelerate the testing of different nano-antenna arrangements. Because of the numerous antennas and their interactions with light, this sort of simulation can require "massive amounts of memory and time," according to Colburn. He developed a method for efficiently simulating metasurfaces' picture-making capabilities without sacrificing accuracy.


The metasurfaces were created by co-author James Whitehead, a PhD student at the University of Washington, who utilized silicon nitride, a glass-like material known to be compatible with common semiconductor manufacturing processes. This implies that a metasurface design may be readily manufactured in lower cost than conventional camera lenses.


Although the concept of using a surface optical technology in the front end and neural-based processing in the back is not new, it's the first to do so, according to Joseph Mait, a consultant with Mait-Optik and former senior researcher and chief scientist at the US Army Research Laboratory.


"Completing the Herculean challenge to develop the million features, shape, and location of the metasurface as well as the post-detection processing parameters to obtain the desired imaging performance is a significant achievement," said Mait.

The researchers are currently working on enhancing the camera's computational abilities. Beyond improving picture quality, they want to add vision capabilities for object detection and other sensing modalities relevant to medicine and robotics.


Heide also foresees employing ultracompact imagers to fabricate complete surfaces that function as sensors in the future: "We may transform individual surfaces into cameras with ultra-high resolution, so you won't need three cameras on the back of your phone anymore, but the whole phone's back would become one enormous camera. "We can imagine many different ways to construct devices in the future," he added.





Manifest Destiny Techniques by Billy Carson with Author Justin Carson



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About the Blogger:


April Carson is the daughter of Billy Carson. She received her bachelor's degree in Social Sciences from Jacksonville University, where she was also on the Women's Basketball team. She now has a successful clothing company that specializes in organic baby clothes and other items. Take a look at their most popular fall fashions on bossbabymav.com


To read more of April's blogs, check out her website! She publishes new blogs on a daily basis, including the most helpful mommy advice and baby care tips! Follow on IG @bossbabymav


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