• Acta Physica Sinica
  • Vol. 69, Issue 18, 184202-1 (2020)
Bin Liu, Peng-Xiang Zhao, Xia Zhao*, Yue Luo, and Li-Chao Zhang
Author Affiliations
  • School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
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    DOI: 10.7498/aps.69.20200471 Cite this Article
    Bin Liu, Peng-Xiang Zhao, Xia Zhao, Yue Luo, Li-Chao Zhang. Multiple aperture underwater imaging algorithm based on polarization information fusion[J]. Acta Physica Sinica, 2020, 69(18): 184202-1 Copy Citation Text show less
    Simulated turbid underwater multiple aperture imaging experiment scene.
    Fig. 1. Simulated turbid underwater multiple aperture imaging experiment scene.
    Comparison of simulated turbid underwater target image recovery results. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) The polarization degree distribution and background scattering estimated by the fitting method; (b1), (b2) refocusing estimation of polarization degree distribution and background scattering; (c1), (c2) horizontally polarized image; (d1), (d2) vertically polarized images; (e1), (e2) image restoration by fitting method; (f1), (f2) image recovery from reference perspective; (g1), (g2) multi-perspective fusion to restore the image.
    Fig. 2. Comparison of simulated turbid underwater target image recovery results. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) The polarization degree distribution and background scattering estimated by the fitting method; (b1), (b2) refocusing estimation of polarization degree distribution and background scattering; (c1), (c2) horizontally polarized image; (d1), (d2) vertically polarized images; (e1), (e2) image restoration by fitting method; (f1), (f2) image recovery from reference perspective; (g1), (g2) multi-perspective fusion to restore the image.
    Comparison of simulated different turbid concentrations underwater target image recovery results. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) Images in clear water; (b1), (b2) the restoration image corresponding to concentration 1; (c1), (c2) the restoration image corresponding to concentration 2; (d1), (d2) the restoration image corresponding to concentration 3; (e1), (e2) the restoration image corresponding to concentration 4.
    Fig. 3. Comparison of simulated different turbid concentrations underwater target image recovery results. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) Images in clear water; (b1), (b2) the restoration image corresponding to concentration 1; (c1), (c2) the restoration image corresponding to concentration 2; (d1), (d2) the restoration image corresponding to concentration 3; (e1), (e2) the restoration image corresponding to concentration 4.
    Comparison of simulated underwater target image recovery results with different sediment concentrations. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) Image of clear water; (b1), (b2) the restoration image corresponding to sediment concentration 1; (c1), (c2) the restoration image corresponding to sediment concentration 2; (d1), (d2) the restoration image corresponding to sediment concentration 3.
    Fig. 4. Comparison of simulated underwater target image recovery results with different sediment concentrations. Up panel: Doll image recovery results. Down panel: Metal coin image recovery results. (a1), (a2) Image of clear water; (b1), (b2) the restoration image corresponding to sediment concentration 1; (c1), (c2) the restoration image corresponding to sediment concentration 2; (d1), (d2) the restoration image corresponding to sediment concentration 3.
    目标PSNRSSIM
    拟合法参数估计 重建结果 参考视角 恢复结果 多视角融合 重建结果 拟合法参数估计 重建结果 参考视角 恢复结果 多视角融合 重建结果
    玩偶21.431422.524225.82400.73300.83590.8885
    金属币23.069623.958524.55810.72320.83250.8796
    Table 1. Quantitative comparison of experiment 1 results.
    目标PSNRSSIM
    浓度1浓度2浓度3浓度4浓度1浓度2浓度3浓度4
    玩偶25.728325.196024.480623.49750.84910.83950.82610.8175
    金属币25.017223.843922.746621.92430.83800.82200.81720.8041
    Table 2. Quantitative comparison of experiment 2 results.
    目标PSNRSSIM
    泥沙浓度1泥沙浓度2泥沙浓度3泥沙浓度1泥沙浓度2泥沙浓度3
    玩偶24.775523.393021.57480.79450.73030.6863
    金属币23.953122.607220.48580.76100.70300.6184
    Table 3. Quantitative comparison of experiment 3 results.
    Bin Liu, Peng-Xiang Zhao, Xia Zhao, Yue Luo, Li-Chao Zhang. Multiple aperture underwater imaging algorithm based on polarization information fusion[J]. Acta Physica Sinica, 2020, 69(18): 184202-1
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