Laser & Optoelectronics Progress, Volume. 60, Issue 16, 1610001(2023)

SAR Image Sparse Denoising Based on Blind Estimation and Bilateral Filtering

Yu Sun1, Zhihui Xin1、*, Penghui Huang2, Zhixu Wang1, and Jiayu Xuan1
Author Affiliations
  • 1Yunnan Key Laboratory of Opto-Electronic Information Technology, School of Physics and Electronic Information, Yunnan Normal University, Kunming 650500, Yunnan, China
  • 2Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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    Figures & Tables(14)
    Flow chart of the SR-BBF
    Experimental images. (a) Scene 1; (b) scene 2; (c) scene 3
    Denoising results of scene 1. (a) Noise image; (b) Lee filtering; (c) Frost filtering; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    Denoising results of scene 2. (a) Noise image; (b) Lee filtering; (c) Frost filtering; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    Denoising results of scene 3. (a) Noise image; (b) Lee filtering; (c) Frost filtering; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    Noise-adding images under different σ. (a) Original image; (b) σ=0.5; (c) σ=1; (d) σ=1.5
    Denoising results under σ=0.5. (a) Noise image; (b) Lee filtering; (c) Frost filtering; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    Denoising results under σ=1. (a) Noise image; (b) Lee filtering; (c) Frost filtering; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    Denoising results under σ=1.5. (a) Noise image; (b) Lee filtering; (c) Frost filtering ; (d) BM3D filtering; (e) BF; (f) SR; (g) SR-Bayes; (h) proposed method
    • Table 1. Comparison of denoising quality indicators of scene 1

      View table

      Table 1. Comparison of denoising quality indicators of scene 1

      MethodPSNR /dBENLEPISSIM
      Unfiltered21.1820.19
      Lee23.5772.210.630.53
      Frost23.4049.790.700.51
      BM3D23.13120.030.770.56
      BF24.3039.640.870.66
      SR24.5332.260.860.69
      SR-Bayes24.4943.860.790.61
      Proposed method24.94131.020.800.61
    • Table 2. Comparison of denoising quality indicators of scene 2

      View table

      Table 2. Comparison of denoising quality indicators of scene 2

      MethodPSNR /dBENLEPISSIM
      Unfiltered13.6618.05
      Lee14.2375.480.430.51
      Frost14.8458.240.540.52
      BM3D14.6876.260.510.64
      BF15.6641.460.820.79
      SR14.5144.870.740.70
      SR-Bayes15.8981.200.780.68
      Proposed method16.3893.280.800.75
    • Table 3. Comparison of denoising quality indicators of scene 3

      View table

      Table 3. Comparison of denoising quality indicators of scene 3

      MethodPSNR /dBENLEPISSIM
      Unfiltered27.2120.41
      Lee27.2756.010.470.79
      Frost28.0749.090.550.82
      BM3D27.8275.640.500.81
      BF28.3958.160.780.89
      SR27.5570.020.720.85
      SR-Bayes27.4672.430.750.82
      Proposed method28.7287.620.810.83
    • Table 4. Comparison of image quality indicators after filtering under different noise levels

      View table

      Table 4. Comparison of image quality indicators after filtering under different noise levels

      Methodσ=0.5σ=1σ=1.5
      PSNR /dBENLEPISSIMPSNR /dBENLEPISSIMPSNR /dBENLEPISSIM
      Unfiltered24.121.850.540.6921.570.920.370.4420.130.730.300.32
      Lee24.395.590.680.7423.153.680.760.7721.053.910.640.69
      Frost24.834.320.650.8122.582.580.690.6721.372.410.560.55
      BM3D25.096.720.750.7522.534.580.690.6521.375.510.600.62
      BF25.258.190.730.7422.681.750.470.6220.521.090.360.44
      SR25.4023.950.890.8423.2213.070.670.7221.379.090.600.63
      SR-Bayes25.4125.350.900.8523.1611.620.660.7221.429.710.610.63
      Proposed method25.3228.130.900.8323.4016.600.730.7122.2314.780.700.60
    • Table 5. Image blockiness index of the proposed method

      View table

      Table 5. Image blockiness index of the proposed method

      ParameterScene 1Scene 2Scene 3Noise-adding image1Noise-adding image 2Noise-adding image 3
      BI0.0180.0580.0260.0240.0150.058
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    Yu Sun, Zhihui Xin, Penghui Huang, Zhixu Wang, Jiayu Xuan. SAR Image Sparse Denoising Based on Blind Estimation and Bilateral Filtering[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1610001

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    Paper Information

    Category: Image Processing

    Received: Sep. 5, 2022

    Accepted: Oct. 9, 2022

    Published Online: Aug. 15, 2023

    The Author Email: Xin Zhihui (xinzhihui.luncky@163.com)

    DOI:10.3788/LOP222462

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