• Acta Optica Sinica
  • Vol. 45, Issue 6, 0628012 (2025)
Shihua Yang1, Xiaoyong Wang1,*, Xing Liu2, Jinping He1..., Qiang Li1 and Xin Yuan3,**|Show fewer author(s)
Author Affiliations
  • 1Beijing Institute of Space Mechanics and Electricity, Beijing 100094, China
  • 2Zhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Westlake Institute for Optoelectronics, Westlake University, Hangzhou 311421, Zhejiang , China
  • 3School of Engineering, Westlake University, Hangzhou 311421, Zhejiang , China
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    DOI: 10.3788/AOS241467 Cite this Article Set citation alerts
    Shihua Yang, Xiaoyong Wang, Xing Liu, Jinping He, Qiang Li, Xin Yuan. Low-Light Remote Sensing Imaging Technology Based on Video Snapshot Compression Imaging[J]. Acta Optica Sinica, 2025, 45(6): 0628012 Copy Citation Text show less
    Influence mechanism of image motion
    Fig. 1. Influence mechanism of image motion
    Low-light remote sensing simulation. (a) Original image; (b) low-light simulation image
    Fig. 2. Low-light remote sensing simulation. (a) Original image; (b) low-light simulation image
    Remote sensing imaging results based on video SCI. (a) Reconstruction results; (b) modulation masks; (c) video SCI remote sensing camera; (d) compression observation image; (e) dynamic scenes
    Fig. 3. Remote sensing imaging results based on video SCI. (a) Reconstruction results; (b) modulation masks; (c) video SCI remote sensing camera; (d) compression observation image; (e) dynamic scenes
    Simulation results at different integration time. (a) Original image; (b)‒(d) low-light simulation images; (e)‒(h) coded reconstruction images
    Fig. 4. Simulation results at different integration time. (a) Original image; (b)‒(d) low-light simulation images; (e)‒(h) coded reconstruction images
    Fitting curve of integration time and reconstruction SNR
    Fig. 5. Fitting curve of integration time and reconstruction SNR
    Simulation results at different compression ratios (Cr). (a)‒(d) Compression observation images; (e)‒(h) reconstruction results
    Fig. 6. Simulation results at different compression ratios (Cr). (a)‒(d) Compression observation images; (e)‒(h) reconstruction results
    Reconstruction results at different integration time and compression ratios
    Fig. 7. Reconstruction results at different integration time and compression ratios
    Simulation results at different target speeds. (a) Interval of 0 frame; (b) interval of 1 frame; (c) interval of 2 frames; (d) interval of 3 frames
    Fig. 8. Simulation results at different target speeds. (a) Interval of 0 frame; (b) interval of 1 frame; (c) interval of 2 frames; (d) interval of 3 frames
    Principle prototype after packaging
    Fig. 9. Principle prototype after packaging
    Imaging results at different integration time. (a) 33 ms; (b) 50 ms; (c) 100 ms; (d) 200 ms
    Fig. 10. Imaging results at different integration time. (a) 33 ms; (b) 50 ms; (c) 100 ms; (d) 200 ms
    Imaging effect at different compression ratios. (a)(d) Compression ratio is 10; (b)(e) compression ratio is 20; (c)(f) compression ratio is 30
    Fig. 11. Imaging effect at different compression ratios. (a)(d) Compression ratio is 10; (b)(e) compression ratio is 20; (c)(f) compression ratio is 30
    Model parameterSetting
    F-number10
    Sensor pixel area8 μm×8 μm
    Transmittance of optical system0.7
    Quantum efficiency0.6
    ObscurationNone
    Central wavelength600 nm
    GainHigh-gain mode (G=8)
    Camera field angle2.4°
    Table 1. Calculation parameters of the number of photogenerated electrons
    Shihua Yang, Xiaoyong Wang, Xing Liu, Jinping He, Qiang Li, Xin Yuan. Low-Light Remote Sensing Imaging Technology Based on Video Snapshot Compression Imaging[J]. Acta Optica Sinica, 2025, 45(6): 0628012
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