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Hyperspectral imaging provides optical information with high-dimensionalspatial-temporal-spectral data cubes revealing intrinsic mattercharacteristics. It has been widely applied in various intelligent inspectionapplications. The existing hyperspectral imaging systems employ individualoptical prism or grating to separate different spectra, which requirecomplicated optical design that takes a heavy load for integration. Theemerging multispectral imaging sensor integrates narrow-band filters on eachpixel element, wasting most light throughput and trapped in the rigoroustradeoff between spatial and spectral resolution. In this work, we report anon-chip computational hyperspectral imaging framework with full spatial andtemporal resolution. By integrating different broadband filtering materials onthe imaging sensor, the target spectral information is non-uniformly andintrinsically coupled on each pixel with high light throughput. Usingintelligent reconstruction algorithms, multi-channel images can be recoveredfrom each frame, realizing real-time hyperspectral imaging. Following such aframework, we for the first time fabricated a broadband (400-1700 nm)hyperspectral imaging sensor with an average light throughput of 71.8$\%$(enabling 32.5 dB peak signal-to-noise ratio of spectral reconstruction onColorChecker Classic chart) and 89 wavelength channels (10 nm interval within400-1000 nm and 25 nm interval within 1000-1700 nm). The average spectralresolution achieves 2.65 nm at 400-1000 nm and 8.59 nm at 1000-1700 nm. Thedemonstrated spatial resolution is 2048x2048 pixels at 47 fps, with $\sim$3.43arc minute resolving ability at a 39-degree field of view. We employed theprototype sensor to collect a large-scale hyperspectral image dataset (210scenes over 8 categories), and demonstrated the sensor's wide applicationpotentials on a series of experiments ...

A low-cost integrated hyperspectral imaging sensor with full temporal and spatial resolution at VIS-NIR wide range