Video-rate hyperspectral camera based on a CMOS-compatible random array of Fabry-Perot filters

Abstract

Hyperspectral (HS) imaging provides rich spatial and spectral information and extends image inspection beyond human perception. Existing approaches, however, suffer from several drawbacks such as low sensitivity, resolution and/or frame rate, which confines HS cameras to scientific laboratories. Here we develop a video-rate HS camera capable of collecting spectral information on real-world scenes with sensitivities and spatial resolutions comparable with those of a typical RGB camera. Our camera uses compressive sensing, whereby spatial-spectral encoding is achieved with an array of 64 complementary metal-oxide-semiconductor (CMOS)-compatible Fabry-Perot filters placed onto a monochromatic image sensor. The array affords high optical transmission while minimizing the reconstruction error in subsequent iterative image reconstruction. The experimentally measured sensitivity of 45% for visible light, the spatial resolution of 3 px for 3 dB contrast, and the frame rate of 32.3 fps at VGA resolution meet the requirements for practical use. For further acceleration, we show that AI-based image reconstruction affords operation at 34.4 fps and full high-definition resolution. By enabling practical sensitivity, resolution and frame rate together with compact size and data compression, our HS camera holds great promise for the adoption of HS technology in real-world scenarios, including consumer applications such as smartphones and drones.

A hyperspectral camera based on a random array of CMOS-compatible Fabry-Perot filters is demonstrated. The hyperspectral camera exhibits performance comparable with that of a typical RGB camera, with 45% sensitivity to visible light, a spatial resolution of 3 px for 3 dB contrast, and a frame rate of 32.3 fps at VGA resolution.