Abigail Klein Leichman
December 19, 2017

New software developed in Israel enables standard cameras to capture hyperspectral images and video, providing a faster and more cost-efficient approach than what is commercially available today.

Hyperspectral cameras can detect specific materials and identify the qualities of those materials, such as oil or impurities in water. Yet these cameras are expensive, cumbersome and slow. Photographing a single frame can take up to a minute.

“Current hyperspectral technology seeks to capture the entire electromagnetic spectrum,” said Prof. Ohad Ben-Shahar, founding director of the Interdisciplinary Computational Vision Laboratory and head of computer science at Ben-Gurion University of the Negev (BGU).

“Our technology, however, shows that wavelengths in nature cover only a small subset of all possible spectra, since the spectrum of the sun is relatively stable and the number of substances in the world is finite,” Ben-Shahar said.

“Using computational research, we were able to reconstruct hyperspectral imaging from the regular RGB color model used in regular cameras. In most cases, this provides extremely good reconstruction.”

The game-changing software for any kind of camera, including smartphone cameras, captures the spectral signature of every pixel in a single image. Current spectrometric technology, by comparison, can measure only one point or line at a time.

The software also can create hyperspectral videos, instantly collecting hyperspectral information on non-static objects.

The global hyperspectral imaging systems market is projected to reach $12.71 billion by 2021, according to a Markets and Markets Report from January 2017.

BGN Technologies, the technology transfer company of BGU, has patented the invention and is working with the researchers to commercialize it.

“This invention will help make hyperspectral technology more accessible,” said Boaz Arad, a computer science PhD student and co-creator of the project, “expanding its use to new fields such as improved color imagery and light sensitivity in regular photography.”

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