Aperture Diffraction for Compact Snapshot Spectral Imaging

Tao Lv, Hao Ye, Quan Yuan, Zhan Shi, Yibo Wang +2 more
2/14/2026

No official code found. Best implementation: Krito-ex/CSST (11 stars, MIT, last commit 2024-01-09).

Abstract

We demonstrate a compact, cost-effective snapshot spectral imaging system named Aperture Diffraction Imaging Spectrometer (ADIS), which consists only of an imaging lens with an ultra-thin orthogonal aperture mask and a mosaic filter sensor, requiring no additional physical footprint compared to common RGB cameras. Then we introduce a new optical design that each point in the object space is multiplexed to discrete encoding locations on the mosaic filter sensor by diffraction-based spatial-spectral projection engineering generated from the orthogonal mask. The orthogonal projection is uniformly accepted to obtain a weakly calibration-dependent data form to enhance modulation robustness. Meanwhile, the Cascade Shift-Shuffle Spectral Transformer (CSST) with strong perception of the diffraction degeneration is designed to solve a sparsity-constrained inverse problem, realizing the volume reconstruction from 2D measurements with Large amount of aliasing. Our system is evaluated by elaborating the imaging optical theory and reconstruction algorithm with demonstrating the experimental imaging under a single exposure. Ultimately, we achieve the sub-super-pixel spatial resolution and high spectral resolution imaging. The code will be available at: https://github.com/Krito-ex/CSST.

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Code Implementations(1)

Krito-ex/CSSTCommunity100%
MIT

Toolboox for Reconstruction of Aperture Diffraction Imaging Spectrometer(ADIS), and also can be using for solving the inverse prooblem of PSF engineering and RGB SR. This toolkit will be continually refined.

110PythonAug 10, 20232 years agoMIT
psf-engineeringscisnapshotsuper-resolution

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Cite this paper

@article{lv2026aperture,
  title  = {Aperture Diffraction for Compact Snapshot Spectral Imaging},
  author = {Tao Lv and Hao Ye and Quan Yuan and Zhan Shi and Yibo Wang and Shuming Wang and Xun Cao},
  year   = {2026},
  eprint = {2309.16372},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/pdf/2309.16372},
  journal = {ICCV 2023 2023}
}

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