Acta Optica Sinica, Volume. 41, Issue 16, 1628003(2021)

Remote Sensing Image Restoration Method Based on Lorentz Fitting Point Spread Function

Guoxing Huang1, Yipeng Liu1, Hong Peng1、*, Weidang Lu1, and Jingwen Wang2
Author Affiliations
  • 1College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
  • 2College of Information Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China
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    Figures & Tables(21)
    Schematic of two-dimensional Gaussian model
    Defocusing blurred kernel (upper) and its one-dimensional profile (down). (a)(d) Disk model; (b)(e) Airy spot; (c)(f) convolution result
    Estimated actual blurred kernel (right) and its x-axis one-dimensional profile (left). (a)(b) First; (c)(d) second; (e)(f) third
    VPW-function-fitted curves under different parameters
    Fitting results of actual blurred kernel based on different models
    Evaluation results of different kernels. (a) RMSE values; (b) R-square values
    Blurred step edges
    Detection results of edge points
    Detection results of ESF curves. (a)(b) Before interpolation; (c)(d) after interpolation
    R-L image restoration method based on VPW fitting PSF
    Original images and composite blurred kernels
    Restoration results by method in Ref. [20]
    Restoration results by method in Ref. [16]
    Restoration results by method in Ref. [4]
    Restoration results by proposed method
    RMSE fitted by different kernel models
    Restoration results of house image. (a) Actual blurred image; (b) restoration result in Ref. [20]; (c) restoration result in Ref. [16]; (d) restoration result in Ref. [4]; (e) restoration result here
    Restoration results of track image. (a) Actual blurred image; (b) restoration result in Ref. [20]; (c) restoration result in Ref. [16]; (d) restoration result in Ref. [4]; (e) restoration result here
    Restoration results of harbor image. (a) Actual blurred image; (b) restoration result in Ref. [20]; (c) restoration result in Ref. [16]; (d) restoration result in Ref. [4]; (e) restoration result here
    • Table 1. Restoration effect comparison of composite images

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      Table 1. Restoration effect comparison of composite images

      MethodImage 1Image 2Image 3
      GMGSSIMGMGSSIMGMGSSIM
      Actual image3.210.553.340.532.880.61
      Method in Ref. [20]5.330.654.970.734.440.72
      Method in Ref. [16]5.280.724.430.774.310.79
      Method in Ref. [4]5.740.814.580.794.610.81
      Proposed method6.350.914.820.874.980.86
    • Table 2. Restoration effect comparison of real images

      View table

      Table 2. Restoration effect comparison of real images

      MethodHouseTrackHarbor
      GMGSSIMGMGSSIMGMGSSIM
      Actual image2.261.002.941.003.181.00
      Method in Ref. [20]6.120.783.870.746.030.77
      Method in Ref. [16]4.560.634.690.664.810.59
      Method in Ref. [4]4.980.594.880.615.440.57
      Proposed method5.770.545.620.566.210.55
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    Guoxing Huang, Yipeng Liu, Hong Peng, Weidang Lu, Jingwen Wang. Remote Sensing Image Restoration Method Based on Lorentz Fitting Point Spread Function[J]. Acta Optica Sinica, 2021, 41(16): 1628003

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jan. 27, 2021

    Accepted: Mar. 18, 2021

    Published Online: Aug. 12, 2021

    The Author Email: Peng Hong (ph@zjut.edu.cn)

    DOI:10.3788/AOS202141.1628003

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