• Advanced Photonics Nexus
  • Vol. 3, Issue 6, 066004 (2024)
Libang Chen1, Jun Yang1, Lingye Chen1, Yuyang Shui2..., Yikun Liu1,2,* and Jianying Zhou2|Show fewer author(s)
Author Affiliations
  • 1Sun Yat-Sen University (Zhuhai Campus), Guangdong Provincial Key Laboratory of Quantum Metrology and Sensing, School of Physics and Astronomy, Zhuhai, China
  • 2Sun Yat-Sen University, State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Guangzhou, China
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    DOI: 10.1117/1.APN.3.6.066004 Cite this Article Set citation alerts
    Libang Chen, Jun Yang, Lingye Chen, Yuyang Shui, Yikun Liu, Jianying Zhou, "Harnessing optical imaging limit through atmospheric scattering media," Adv. Photon. Nexus 3, 066004 (2024) Copy Citation Text show less

    Abstract

    Recording and identifying faint objects through atmospheric scattering media by an optical system are fundamentally interesting and technologically important. We introduce a comprehensive model that incorporates contributions from target characteristics, atmospheric effects, imaging systems, digital processing, and visual perception to assess the ultimate perceptible limit of geometrical imaging, specifically the angular resolution at the boundary of visible distance. The model allows us to reevaluate the effectiveness of conventional imaging recording, processing, and perception and to analyze the limiting factors that constrain image recognition capabilities in atmospheric media. The simulations were compared with the experimental results measured in a fog chamber and outdoor settings. The results reveal good general agreement between analysis and experiment, pointing out the way to harnessing the physical limit for optical imaging in scattering media. An immediate application of the study is the extension of the image range by an amount of 1.2 times with noise reduction via multiframe averaging, hence greatly enhancing the capability of optical imaging in the atmosphere.
    mdMTFsys=mdimgmax{kmdnoise,1Γ},

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    md=IWIBIW+IB=rWrBrW+rB,

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    MTFsys=MTFAMTFLMTFS,

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    MTFA=12exp(τ)1exp{3.44(λfνr0)53[10.5(λνD)13]},

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    MTFL=exp[π2δ24ln(2)ν2],

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    MTFs=exp[2π2(Ls6)2ν2],

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    mdnoise=|F(n)|n,

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    α=π4(δ2ln2+29Ls2)ln{kmd|F(n)|n[2exp(τ)1]},

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    AR=2arctan(αf),

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    τmax=ln2+ln(mdΓ+1).

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    Varience=(nn)2,

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    R2=1Σi=1data(yiyipred)2Σi=1data(yiy)2,

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    RMSE=1dataΣi=1data(yiyipred)2,

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    dIr(x,y,z)dz=βextIr(x,y,z)+βscaA+ΔIsa(x,y,dz),

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    Ir(x,y,L)=exp(τ)[Ir(x,y,0)βscaAβext]+βscaA/βext+Isa(x,y,L).

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    md(τ)=md1+2βscaβext(rW+rB)[exp(τ)1].

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    md(τ)=md(0)2exp(τ)1.

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    MTFAE=12exp(τ)1.

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    MTFTU=exp{3.44(λfνr0)53[10.5(λνD)13]},

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    δ=1.025λDf,

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    PSFL(r)=exp[r22(δ/22ln2)].

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    MTFL=exp[π2δ24ln(2)ν2].

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    PSFS=exp[r22(Ls/6)2],

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    MTFS=exp[2π2(Ls/6)2ν2].

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