Acta Photonica Sinica, Volume. 52, Issue 4, 0410001(2023)

Image Restoration Method of Synthetic Aperture Optical System Based on Sparse Prior

Shuo ZHONG1,2, Bin FAN1、*, Dun LIU1, Haibing SU1, Hao ZHANG1,2, Hu YANG1, and Artem NIKONOROV3
Author Affiliations
  • 1General Laboratory of Film Camera, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209,China
  • 2University of Chinese Academy of Sciences, Beijing 100019, China
  • 3Samara National Research University, Samara 443086, Russia
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    Figures & Tables(17)
    Comparison between synthetic aperture system and single aperture system
    Flow chart of image restoration method
    Dark channel comparison between original image and degraded image
    Dark channel statistics of clear and blurred images
    Dark channel matrix mapping
    The first group of experimental results(iterations in parentheses)
    Results in different scenes
    Image acquisition
    Restoration results of captured remote sensing image
    Restoration results of captured real image
    • Table 0. [in Chinese]

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      Table 0. [in Chinese]

      Algorithm 1 Deblurring Algorithm

      Input:Blurred image G,Initialize h with PSF

      for i=1:iteration do

      I=Gω=2λ

      repeat

      solve for p using Eq.(18)

        μ=2 β

        repeat

         solve for g using Eq.(17)

         solve for latent image I using Eq.(15)

         μ=2 μ

        until μ>μmax

        ω=2ω

       until ω>ωmax

       solve for blur kernel h using Eq.(11)

      β=0.9 βλ=0.9 λ

      end for

      Output:blur kernel h,result image I

    • Table 1. Table of piston error corresponding to sub hole diameters of different groups

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      Table 1. Table of piston error corresponding to sub hole diameters of different groups

      Aperture position2345678
      Group 10.10λ0.11λ0.03λ0.25λ0.16λ0.08λ0.06λ
      Group 20.18λ0.27λ0.02λ0.02λ0.19λ0.23λ0.13λ
      Group 30.23λ0.06λ0.26λ0.07λ0.06λ0.10λ0.12λ
      Group 40.28λ0.02λ0.09λ0.06λ0.05λ0.29λ0.27λ
      Group 50.06λ0.20λ0.11λ0.19λ0.01λ0.21λ0.17λ
    • Table 2. Average results of image restoration evaluation indicators for different piston errors(variance in parentheses)

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      Table 2. Average results of image restoration evaluation indicators for different piston errors(variance in parentheses)

      Degraded imageWF methodRL methodProposed method
      1358
      PSNR/dB/19.31(0.03)17.94(0.07)16.78(0.11)22.83(0.06)23.13(0.02)23.200.02
      SSIM/0.70(0.000 3)0.64(0.000 4)0.70(0.000 6)0.75(0.000 7)0.770.000 30.76(0.000 4)
      GMG6.9914.27(0.407)18.71(0.387)19.22(0.339)19.99(0.254)20.31(0.106)20.430.101
      Time/s/0.0060.151.153.395.669.94
    • Table 3. Average results of image restoration evaluation indicators in different scenes (variance in parentheses)

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      Table 3. Average results of image restoration evaluation indicators in different scenes (variance in parentheses)

      Degraded imageWF methodRL methodProposed method
      PSNR/dB/20.50(5.23)16.98(3.65)23.791.91
      SSIM/0.71(0.003 4)0.72(0.002 2)0.800.001 8
      GMG10.2924.19(21.3)28.98(18.9)30.2817.1
    • Table 4. Optical parameters of camera

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      Table 4. Optical parameters of camera

      ApertureFocal lengthField angleSpectral bandwidthAngular resolutionImaging rangeWavefront aberration(RMS)
      Parameter80 mm641.6 mm0.47°×0.63°486~656 nm686 μrad100 m-∞0.048 6 λ
    • Table 5. Average results of image restoration evaluation indicators of remote sensing(variance in parentheses)

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      Table 5. Average results of image restoration evaluation indicators of remote sensing(variance in parentheses)

      Degraded imageWF methodRL methodProposed method
      PSNR/dB/17.25(2.1215.29(2.85)23.04(2.17)
      SSIM/0.55(0.009 1)0.60(0.003 20.65(0.013)
      GMG5.8918.87(13.54)35.689.824.58(11.3)
    • Table 6. Results of restoration evaluation indicators of real image

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      Table 6. Results of restoration evaluation indicators of real image

      Degraded imageWFRLProposed method
      PSNR/dB/16.1916.0924.11
      SSIM/0.840.690.90
      GMG6.3813.2318.1115.27
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    Shuo ZHONG, Bin FAN, Dun LIU, Haibing SU, Hao ZHANG, Hu YANG, Artem NIKONOROV. Image Restoration Method of Synthetic Aperture Optical System Based on Sparse Prior[J]. Acta Photonica Sinica, 2023, 52(4): 0410001

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    Paper Information

    Category:

    Received: Oct. 20, 2022

    Accepted: Dec. 21, 2022

    Published Online: Jun. 21, 2023

    The Author Email: Bin FAN (fanbin@ioe.ac.cn)

    DOI:10.3788/gzxb20235204.0410001

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