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

Yuexi Zhang; Xiang Chen; Zhaohua Yang; Liejiang Wei; Xuchao Liu; Ling-An Wu

doi:10.1117/12.3039248

13 September 2024 Parallel single-pixel compressive imaging with hyperspectral resolution in the near-infrared band

Yuexi Zhang, Xiang Chen, Zhaohua Yang, Liejiang Wei, Xuchao Liu, Ling-An Wu

Proceedings Volume 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024); 132541N (2024) https://doi.org/10.1117/12.3039248
Event: Fourth International Conference on Optics and Image Processing (ICOIP 2024), 2024, Chongqing, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuexi Zhang, Xiang Chen, Zhaohua Yang, Liejiang Wei, Xuchao Liu, and Ling-An Wu "Parallel single-pixel compressive imaging with hyperspectral resolution in the near-infrared band", Proc. SPIE 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024), 132541N (13 September 2024); https://doi.org/10.1117/12.3039248

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KEYWORDS

Image restoration

Matrices

Sampling rates

Image quality

Hyperspectral imaging

Imaging spectroscopy

Modulation

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