Turn off MathJax
Article Contents
Minda Qiao, Yuhan Zhang, Haodong Yang, Linge Bai, Xue Dong, Tong Zhang, Jinpeng Liu, Fei Liu, Sylvain Gigan, Xiaopeng Shao. Harnessing forward scattering effect for high dynamic imaging[J]. PhotoniX. doi: 10.1186/s43074-025-00202-6
Citation: Minda Qiao, Yuhan Zhang, Haodong Yang, Linge Bai, Xue Dong, Tong Zhang, Jinpeng Liu, Fei Liu, Sylvain Gigan, Xiaopeng Shao. Harnessing forward scattering effect for high dynamic imaging[J]. PhotoniX. doi: 10.1186/s43074-025-00202-6

Harnessing forward scattering effect for high dynamic imaging

doi: 10.1186/s43074-025-00202-6
Funds:  The work was supported by National Natural Science Foundation of China (NSFC) (62105254, 62205259, 62375212, and 62405231), Fundamental Research Funds for the Central Universities (XJSJ24028, XJS222202, and YJSJ25010), Science Fund for Distinguished Young Scholars of Shaanxi Province (2024JC-JCQN-60), National Key Laboratory of Space Target Awareness, and Innovation Fund of Xidian University.
  • Received Date: 2025-03-10
  • Accepted Date: 2025-09-24
  • Rev Recd Date: 2025-09-11
  • Available Online: 2025-10-16
  • Imaging scenes with a high dynamic range (HDR) of light intensities is critical for applications such as biomedical imaging, astronomical observation, and industrial automation, where accurate detection of both bright and dark regions is essential for precise analysis and decision-making. In this paper, we propose an HDR imaging approach harnessing optical forward scattering effect that breaks the limitations of image processing type. Our approach integrates a nonlinear deconvolution method based on speckle background noise estimation, along with Cross-correlation and Laplacian pyramid fusion method, to improve imaging precision and adaptability. By utilizing a digital micromirror device and a scattering diffuser, we develop a proof-of-concept experimental system, validating the effectiveness of reconstruction of faint details in HDR scenes. This method achieves dynamic range expansion from a 130.01 dB HDR scene using a detector with an 88.5 dB dynamic range, achieving a 119-fold intensity difference. Our work demonstrates a promising new solution for HDR imaging in demanding lighting environments, which could expand the scope of photoelectronic imaging application.
  • loading
  • [1]
    Liu Y, Gao C, Li D, et al. Dynamic X-ray imaging with screen-printed perovskite CMOS array. Nat Commun. 2024;15(1):1588. https://doi.org/10.1038/s41467-024-45871-2.
    [2]
    Du S, Dong Z, Li Y, Ikenaga T. Straight-line detection within 1 millisecond per frame for ultrahigh-speed industrial automation. IEEE Trans Ind Inform. 2023;19(4):5965–75. https://doi.org/10.1109/TII.2022.3170585.
    [3]
    Long Z, Qiu X, Chan CLJ, et al. A neuromorphic bionic eye with filter-free color vision using hemispherical perovskite nanowire array retina. Nat Commun. 2023;14(1):1972. https://doi.org/10.1038/s41467-023-37581-y.
    [4]
    Daly S, Ferreira Fernandes J, Bruggeman E, et al. High-density volumetric super-resolution microscopy. Nat Commun. 2024;15(1):1940. https://doi.org/10.1038/s41467-024-45828-5.
    [5]
    Vinegoni C, Leon Swisher C, Fumene Feruglio P, et al. Real-time high dynamic range laser scanning microscopy. Nat Commun. 2016;7(1):11077. https://doi.org/10.1038/ncomms11077.
    [6]
    Zhao W, Zhao S, Li L, et al. Sparse deconvolution improves the resolution of live-cell super-resolution fluorescence microscopy. Nat Biotechnol. 2022;40(4):606–17. https://doi.org/10.1038/s41587-021-01092-2.
    [7]
    Guilbert J, Negash A, Labouesse S, Gigan S, Sentenac A, Aguiar HB de. Label-free super-resolution stimulated Raman scattering imaging of biomedical specimens. ai. 2024;1(1):011004. https://doi.org/10.3788/AI.2024.10004.
    [8]
    Jin D, Chen Y, Lu Y, et al. Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning. Nat Mach Intell. 2021;3(10):876–84. https://doi.org/10.1038/s42256-021-00392-1.
    [9]
    Liu T, Quan Y, Su Y, et al. Astronomical image denoising by self-supervised deep learning and restoration processes. Nat Astron. 2025. https://doi.org/10.1038/s41550-025-02484-z.
    [10]
    Ho Eom B, Day PK, LeDuc HG, Zmuidzinas J. A wideband, low-noise superconducting amplifier with high dynamic range. Nat Phys. 2012;8(8):623–7. https://doi.org/10.1038/nphys2356.
    [11]
    Pierre A, Gaikwad A, Arias AC. Charge-integrating organic heterojunction phototransistors for wide-dynamic-range image sensors. Nat Photon. 2017;11(3):193–9. https://doi.org/10.1038/nphoton.2017.15.
    [12]
    Jin W, Cao Y, Yang F, Ho HL. Ultra-sensitive all-fibre photothermal spectroscopy with large dynamic range. Nat Commun. 2015;6(1):6767. https://doi.org/10.1038/ncomms7767.
    [13]
    Daulay O, Liu G, Ye K, et al. Ultrahigh dynamic range and low noise figure programmable integrated microwave photonic filter. Nat Commun. 2022;13(1):7798. https://doi.org/10.1038/s41467-022-35485-x.
    [14]
    Mertens T, Kautz J, Van Reeth F. Exposure fusion. In: 15th Pacific Conference on Computer Graphics and Applications (PG’07). IEEE. 2007:382–390. https://doi.org/10.1109/PG.2007.17.
    [15]
    Mertens T, Kautz J, Van Reeth F. Exposure fusion: a simple and practical alternative to high dynamic range photography. Computer Graphics Forum. 2009;28(1):161–71. https://doi.org/10.1111/j.1467-8659.2008.01171.x.
    [16]
    Kodgirwar S, Loetgering L, Liu C, et al. Bayesian multi-exposure image fusion for robust high dynamic range ptychography. Opt Express. 2024;32(16):28090–9. https://doi.org/10.1364/OE.524284.
    [17]
    Shen X, Wang P, Zhu J, et al. Temporal contrast reduction techniques for high dynamic-range temporal contrast measurement. Opt Express. 2019;27(8):10586–601. https://doi.org/10.1364/OE.27.010586.
    [18]
    Niu B, Qu X, Guan X, Zhang F. Fast HDR image generation method from a single snapshot image based on frequency division multiplexing technology. Opt Express. 2021;29(17):27562–72. https://doi.org/10.1364/OE.434950.
    [19]
    Wang Q, Luo H, Li Z, Ding Y, Xiong W. High dynamic range spatial heterodyne one-dimensional imaging spectroscopy based on a digital micromirror device. Opt Express. 2024;32(13):22067–77. https://doi.org/10.1364/OE.520080.
    [20]
    Guo S, Gallego G. CMax-SLAM: event-based rotational-motion bundle adjustment and SLAM system using contrast maximization. IEEE Trans Robot. 2024;40:2442–61. https://doi.org/10.1109/TRO.2024.3378443.
    [21]
    Maqueda AI, Loquercio A, Gallego G, Garcia N, Scaramuzza D. Event-based vision meets deep learning on steering prediction for self-driving cars. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE. 2018:5419–5427. https://doi.org/10.1109/CVPR.2018.00568.
    [22]
    Gallego G, Delbruck T, Orchard G, et al. Event-based vision: a survey. IEEE Trans Pattern Anal Mach Intell. 2022;44(1):154–80. https://doi.org/10.1109/TPAMI.2020.3008413.
    [23]
    Yu Z, Li H, Zhong T, et al. Wavefront shaping: a versatile tool to conquer multiple scattering in multidisciplinary fields. Innov (Camb). 2022;3(5):100292. https://doi.org/10.1016/j.xinn.2022.100292.
    [24]
    Cheng Z, Li C, Khadria A, Zhang Y, Wang LV. High-gain and high-speed wavefront shaping through scattering media. Nat Photon. 2023;17(4):299–305. https://doi.org/10.1038/s41566-022-01142-4.
    [25]
    Liu J, Feng Y, Wang Y, et al. Future-proof imaging: computational imaging. Adv Imaging. 2024;1(1):012001. https://doi.org/10.3788/AI.2024.20003.
    [26]
    Yu Z, Zhong T, Li H, et al. Long distance all-optical logic operations through a single multimode fiber empowered by wavefront shaping. Photon Res. 2024;12(3):587. https://doi.org/10.1364/PRJ.499523.
    [27]
    Zhang X, Gao J, Gan Y, et al. Different channels to transmit information in scattering media. PhotoniX. 2023;4(1):10. https://doi.org/10.1186/s43074-023-00087-3.
    [28]
    Sun J. Poisson matting. Published August 01, 2004. https://dl.acm.org/doi/abs/10.1145/1186562.1015721.
    [29]
    Korotkova O. Design of weak scattering media for controllable light scattering. Opt Lett. 2015;40(2):284. https://doi.org/10.1364/OL.40.000284.
    [30]
    Ntziachristos V. Going deeper than microscopy: the optical imaging frontier in biology. Nat Methods. 2010;7(8):603–14. https://doi.org/10.1038/nmeth.1483.
    [31]
    Jauregui-Sánchez Y, Penketh H, Bertolotti J. Tracking moving objects through scattering media via speckle correlations. Nat Commun. 2022;13(1):5779. https://doi.org/10.1038/s41467-022-33470-y.
    [32]
    Wang R, Wang G. Single image recovery in scattering medium by propagating deconvolution. Opt Express. 2014;22(7):8114–9. https://doi.org/10.1364/OE.22.008114.
    [33]
    Guo E, Zhu S, Sun Y, Bai L, Zuo C, Han J. Learning-based method to reconstruct complex targets through scattering medium beyond the memory effect. Opt Express, OE. 2020;28(2):2433–46. https://doi.org/10.1364/OE.383911.
    [34]
    Song Y, Li H, Zhai G, He Y, Bian S, Zhou W. Comparison of multichannel signal deconvolution algorithms in airborne LiDAR bathymetry based on wavelet transform. Sci Rep. 2021;11(1):16988. https://doi.org/10.1038/s41598-021-96551-w.
    [35]
    Mukherjee S, Rosen J. Imaging through scattering medium by adaptive non-linear digital processing. Sci Rep. 2018;8(1):10517. https://doi.org/10.1038/s41598-018-28523-6.
    [36]
    Rai MR, Vijayakumar A, Rosen J. Non-linear adaptive three-dimensional imaging with interferenceless coded aperture correlation holography (I-COACH). Opt Express. 2018;26(14):18143. https://doi.org/10.1364/OE.26.018143.
    [37]
    Rai MR, Vijayakumar A, Ogura Y, Rosen J. Resolution enhancement in nonlinear interferenceless COACH with point response of subdiffraction limit patterns. Opt Express. 2019;27(2):391. https://doi.org/10.1364/OE.27.000391.
    [38]
    Anand V, Ng SH, Maksimovic J, et al. Single shot multispectral multidimensional imaging using chaotic waves. Sci Rep. 2020;10(1):13902. https://doi.org/10.1038/s41598-020-70849-7.
    [39]
    Anand V, Ng SH, Katkus T, Juodkazis S. Spatio-spectral-temporal imaging of fast transient phenomena using a random array of pinholes. Adv Photonics Res. 2021;2(2):2000032. https://doi.org/10.1002/adpr.202000032.
    [40]
    Feng S, Kane C, Lee PA, Stone AD. Correlations and fluctuations of coherent wave transmission through disordered media. Phys Rev Lett. 1988;61(7):834–7. https://doi.org/10.1103/PhysRevLett.61.834.
    [41]
    Freund I, Rosenbluh M, Feng S. Memory effects in propagation of optical waves through disordered media. Phys Rev Lett. 1988;61(20):2328–31. https://doi.org/10.1103/PhysRevLett.61.2328.
    [42]
    Freund I, Berkovits R. Surface reflections and optical transport through random media: coherent backscattering, optical memory effect, frequency, and dynamical correlations. Phys Rev B. 1990;41(1):496–503. https://doi.org/10.1103/PhysRevB.41.496.
    [43]
    Berkovits R, Kaveh M. Time-reversed memory effects. Phys Rev B. 1990;41(4):2635–8. https://doi.org/10.1103/PhysRevB.41.2635.
    [44]
    Judkewitz B, Horstmeyer R, Vellekoop IM, Papadopoulos IN, Yang C. Translation correlations in anisotropically scattering media. Nature Phys. 2015;11(8):684–9. https://doi.org/10.1038/nphys3373.
    [45]
    Yao J, Zhao Y, Bu Y, Kong SG, Chan JCW. Laplacian pyramid fusion network with hierarchical guidance for infrared and visible image fusion. IEEE Trans Circuits Syst Video Technol. 2023;33(9):4630–44. https://doi.org/10.1109/TCSVT.2023.3245607.
    [46]
    Luo X, Fu G, Yang J, Cao Y, Cao Y. Multi-modal image fusion via deep Laplacian pyramid hybrid network. IEEE Trans Circuits Syst Video Technol. 2023;33(12):7354–69. https://doi.org/10.1109/TCSVT.2023.3281462.
    [47]
    Wang D, Sahoo SK, Zhu X, Adamo G, Dang C. Non-invasive super-resolution imaging through dynamic scattering media. Nat Commun. 2021;12(1):3150. https://doi.org/10.1038/s41467-021-23421-4.
    [48]
    Zhang T, Wang X, Zhao W, Zhai A, Dang C, Wang D. Noninvasive imaging through scattering media with enlarged FOV using PSF estimations and correlations. Adv Photonics Res. 2023;4(6):2300100. https://doi.org/10.1002/adpr.202300100.
    [49]
    Sun S, Gu JH, Lin HZ, Jiang L, Liu WT. Gradual ghost imaging of moving objects by tracking based on cross correlation. Opt Lett. 2019;44(22):5594–7. https://doi.org/10.1364/OL.44.005594.
    [50]
    Li L, Li Q, Sun S, Lin HZ, Liu WT, Chen PX. Imaging through scattering layers exceeding memory effect range with spatial-correlation-achieved point-spread-function. Opt Lett. 2018;43(8):1670–3. https://doi.org/10.1364/OL.43.001670.
    [51]
    Cua M, Zhou E, Haojiang, Yang C. Imaging moving targets through scattering media. Opt Express. 2017;25(4):3935. https://doi.org/10.1364/OE.25.003935.
    [52]
    Sahoo SK, Tang D, Dang C. Single-shot multispectral imaging with a monochromatic camera. Optica. 2017;4(10):1209. https://doi.org/10.1364/OPTICA.4.001209.
    [53]
    Liu J, Yang W, Song G, Gan Q. Directly and instantly seeing through random diffusers by self-imaging in scattering speckles. PhotoniX. 2023;4(1):1. https://doi.org/10.1186/s43074-022-00080-2.
    [54]
    Yang H, Yuan Z, Wang H, Cheng L. An end-to-end network for multiple scattering media imaging. In: Lu Y, Cheng C, eds. Third International Conference on Computer Science and Communication Technology (ICCSCT 2022). SPIE. 2022:162. https://doi.org/10.1117/12.2662207.
    [55]
    Yang B, Tan L, Zhang X, et al. Learning-based polarization retrieval from intensity speckle of dense scattering media. Opt Express. 2025;33(5):9446. https://doi.org/10.1364/OE.555500.
    [56]
    Guo E, Sun Y, Zhu S, et al. Single-shot color object reconstruction through scattering medium based on neural network. Opt Lasers Eng. 2021;136:106310. https://doi.org/10.1016/j.optlaseng.2020.106310.
    [57]
    Li H, Yu Z, Zhao Q, et al. Learning-based super-resolution interpolation for sub-Nyquist sampled laser speckles. Photon Res. 2023;11(4):631. https://doi.org/10.1364/PRJ.472512.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (14) PDF downloads(0) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return