Acta Photonica Sinica, Volume. 49, Issue 2, 0210001(2020)

Sparse Prior-based Space Objects Image Blind Inversion Algorithm

Zheng-zhou LI1...2,3,4, Lin QING1,2, Bo LI1,2, Cheng CHEN1,2, and Bo QI34 |Show fewer author(s)
Author Affiliations
  • 1College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
  • 2Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044, China
  • 3Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
  • 4Key Laboratory of Beam Control, Chinese Academy of Sciences, Chengdu 610209, China
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    Figures & Tables(16)
    Intensity histogram and gradient histogram images of space object in deep space background
    Intensity histogram and gradient histogram images of space object at different exposure levels
    Intensity histogram and gradient histogram images of space object in ground background
    Fitting the gradient distribution of space object image with each prior
    Sparse representation of space object image
    海事卫星图像高斯退化反演结果比较Compare of inversion results of Gaussian degraded maritime satellite image
    空间站图像高斯退化反演结果比较Compare of inversion results of Gaussian degraded space station image
    海事卫星图像运动退化反演结果比较Compare of inversion results of motion degraded maritime satellite image
    空间站图像运动退化反演结果比较Compare of inversion results of motion degraded space station image
    月球观测图像反演结果比较Compare of inversion results of lunar observation image
    土星退化图像反演结果比较Compare of inversion results of real Saturn degraded image
    • Table 1. SSIM and GMG of the inversion results of Gaussian degraded maritime satellite image

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      Table 1. SSIM and GMG of the inversion results of Gaussian degraded maritime satellite image

      Standard deviation of Gaussian blur kernelSSIM/GMG
      Krishnan’sZhang’sPerrone’sPan’sLin’sOur method
      σ=10.868/2.3690.862/3.4450.857/3.5800.931/4.0010.890/4.1330.938/3.542
      σ=20.868/1.7800.873/2.3910.864/2.3140.923/2.3620.917/2.6120.928/2.632
      σ=30.884/1.5050.866/2.0150.865/1.6390.906/2.0780.901/2.0530.918/2.264
      σ=40.878/1.4230.869/1.9080.864/1.6700.879/1.8770.890/1.9970.914/2.116
      σ=50.874/1.3930.845/1.8860.863/1.7870.857/1.8540.904/2.0360.902/1.894
    • Table 2. SSIM and GMG of the inversion results of Gaussian degraded space station image

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      Table 2. SSIM and GMG of the inversion results of Gaussian degraded space station image

      Standard deviation of Gaussian blur kernelSSIM/GMG
      Krishnan’sZhang’sPerrone’sPan’sLin’sOur method
      σ=10.873/8.6170.776/8.6560.515/9.4420.903/9.3480.926/9.7840.947/9.981
      σ=20.795/4.0740.808/5.3990.565/4.9400.833/4.8350.849/5.5580.857/5.620
      σ=30.734/3.6400.710/4.7340.558/4.2000.772/4.6540.801/4.8110.824/4.665
      σ=40.695/5.1950.757/4.3970.549/4.7660.652/5.8290.829/5.1210.806/4.746
      σ=50.674/5.0130.685/4.4830.548/5.0690.636/6.3830.824/5.0050.834/4.955
    • Table 3. SSIM and GMG of the inversion results of motion degraded maritime satellite image

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      Table 3. SSIM and GMG of the inversion results of motion degraded maritime satellite image

      Blur scale of motion blurSSIM/GMG
      Krishnan’sZhang’sPerrone’sPan’sLin’sOur method
      90.859/3.9340.885/3.5320.841/3.7060.891/4.1260.936/4.0630.951/3.983
      130.875/3.3690.863/3.1870.856/3.1630.850/3.7110.928/3.6270.935/3.814
      170.876/3.6170.859/3.0590.853/2.9980.822/3.4340.916/3.5610.921/3.729
      210.820/3.1430.852/2.9160.854/2.9530.799/3.4550.913/3.4850.915/3.492
      250.815/3.2480.846/2.7130.853/2.6520.814/3.1790.904/3.2590.898/3.310
    • Table 4. SSIM and GMG of the inversion results of motion degraded space station image

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      Table 4. SSIM and GMG of the inversion results of motion degraded space station image

      Standard deviation of Gaussian blur kernelSSIM/GMG
      Krishnan’sZhang’sPerrone’sPan’sLin’sOur method
      90.719/5.4800.799/7.2270.515/8.1040.652/8.1310.842/8.7610.869/8.794
      130.649/4.8190.763/6.4900.520/8.1900.627/7.9420.807/8.1750.844/8.203
      170.615/6.6080.752/5.5680.531/6.8620.550/7.7700.836/6.8420.850/6.711
      210.567/5.9670.741/5.4020.546/6.8210.495/7.1080.847/6.8590.851/6.617
      250.543/5.9750.726/4.8890.547/6.0000.493/5.8590.813/5.7580.836/6.294
    • Table 5. Objective evaluation results of the estimated real space object image

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      Table 5. Objective evaluation results of the estimated real space object image

      Degraded imageEvaluation indexesKrishnan’sZhang’sPerrone’sPan’sLin’sOurs
      lunar imageGMG2.8182.8452.8202.6852.8643.2642.8092.5802.8493.1102.8973.623
      Saturn imageGMG3.719 22.924 93.648 52.698 53.742 93.012 43.530 32.407 903.644 92.700 83.729 84.328 6
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    Zheng-zhou LI, Lin QING, Bo LI, Cheng CHEN, Bo QI. Sparse Prior-based Space Objects Image Blind Inversion Algorithm[J]. Acta Photonica Sinica, 2020, 49(2): 0210001

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    Paper Information

    Received: Aug. 29, 2019

    Accepted: Nov. 11, 2019

    Published Online: Mar. 19, 2020

    The Author Email:

    DOI:10.3788/gzxb20204902.0210001

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