Parallel single-pixel compressive imaging with hyperspectral resolution in the near-infrared band

Infrared hyperspectral cameras are complicated in structure, require a large amount of imaging data, and the array detector is expensive, which is not conducive to the efficient imaging and real-time data analysis of objects in the infrared regime. Single pixel imaging offers a solution by employing compressed sampling. This paper describes the design and real time operation of a parallel single-pixel near infrared hyperspectral imaging system which can obtain a 128×128×256 spectral cube image with a spectral resolution of 4 nm within the range of 975 to 1736 nm. The compression rate and reconstructed image quality using different orderings of the Hadamard modulation basis, including the natural, cake cutting, and the Russian dolls sequences, are compared. A good reconstructed image of a dynamic object can be realized even with a compression sampling rate as low as 0.78% with the Russian doll sequence. The method proposed in this paper should have many potential applications due to its efficient sampling and high-speed reconstruction enabled by parallel spectral channel computation.