New Camera at the size of a Salt Grain

Researchers at Princeton University and the University of Washington have developed an ultracompact camera the size of a coarse grain of salt.

The system 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.

Micro-sized cameras have great potential to spot problems in the human body and enable sensing for super-small robots, but past approaches captured fuzzy, distorted images with limited fields of view.

Now, researchers at Princeton University and the University of Washington have overcome these obstacles with an ultracompact camera the size of a coarse grain of salt. The new system can produce crisp, full-color images on par with a conventional compound camera lens 500,000 times larger in volume, the researchers reported in a paper published Nov. 29 in Nature Communications.

Enabled by a joint design of the camera’s 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. Arrays of thousands of such cameras could be used for full-scene sensing, turning surfaces into cameras.

While a traditional camera uses a series of curved glass or plastic lenses to bend light rays into focus, the new optical system relies on a technology called a metasurface, which can be produced much like a computer chip. Just half a millimeter wide, the metasurface is studded with 1.6 million cylindrical posts, each roughly the size of the human immunodeficiency virus (HIV).

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.

Each post has a unique geometry, and 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, the posts’ interactions with light combine to produce the highest-quality images and widest field of view for a full-color metasurface camera developed to date.

Images courtesy of the researchers

source Princeton University