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Computational imaging of moving objects obscured by a random corridor via speckle correlations

Author

Listed:
  • Tian Shi

    (Beijing Institute of Technology
    Science and Technology on Electromagnetic Scattering Laboratory)

  • Liangsheng Li

    (Science and Technology on Electromagnetic Scattering Laboratory)

  • He Cai

    (Science and Technology on Electromagnetic Scattering Laboratory)

  • Xianli Zhu

    (Science and Technology on Electromagnetic Scattering Laboratory)

  • Qingfan Shi

    (Beijing Institute of Technology)

  • Ning Zheng

    (Beijing Institute of Technology)

Abstract

Computational imaging makes it possible to reconstruct hidden objects through random media and around corners, which is of fundamental importance in various fields. Despite recent advances, computational imaging has not been studied in certain types of random scenarios, such as tortuous corridors filled with random media. We refer to this category of complex environment as a ’random corridor’, and propose a reduced spatial- and ensemble-speckle intensity correlation (RSESIC) method to image a moving object obscured by a random corridor. Experimental results show that the method can reconstruct the image of a centimeter-sized hidden object with a sub-millimeter resolution by a low-cost digital camera. The imaging capability depends on three system parameters and can be characterized by the correlation fidelity (CF). Furthermore, the RSESIC method is able to recover the image of objects even for a single pixel containing the contribution of about 102 speckle grains, which overcomes the theoretical limitation of traditional speckle imaging methods. Last but not least, when the power attenuation of speckle intensity leads to serious deterioration of CF, the image of hidden objects can still be reconstructed by the corrected intensity correlation.

Suggested Citation

  • Tian Shi & Liangsheng Li & He Cai & Xianli Zhu & Qingfan Shi & Ning Zheng, 2022. "Computational imaging of moving objects obscured by a random corridor via speckle correlations," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31669-7
    DOI: 10.1038/s41467-022-31669-7
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    References listed on IDEAS

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    1. Freund, Isaac, 1990. "Looking through walls and around corners," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 168(1), pages 49-65.
    2. M. Batarseh & S. Sukhov & Z. Shen & H. Gemar & R. Rezvani & A. Dogariu, 2018. "Passive sensing around the corner using spatial coherence," Nature Communications, Nature, vol. 9(1), pages 1-6, December.
    3. Matthew O’Toole & David B. Lindell & Gordon Wetzstein, 2018. "Confocal non-line-of-sight imaging based on the light-cone transform," Nature, Nature, vol. 555(7696), pages 338-341, March.
    4. Charles Saunders & John Murray-Bruce & Vivek K Goyal, 2019. "Computational periscopy with an ordinary digital camera," Nature, Nature, vol. 565(7740), pages 472-475, January.
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    Cited by:

    1. Yaoyao Shi & Wei Sheng & Yangyang Fu & Youwen Liu, 2023. "Overlapping speckle correlation algorithm for high-resolution imaging and tracking of objects in unknown scattering media," Nature Communications, Nature, vol. 14(1), pages 1-8, December.

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