Acta Optica Sinica (Online), Volume. 2, Issue 15, 1514002(2025)

Oil Spill Detection Methods on Water Surface Based on Multi-Dimension Optical Remote Sensing Imaging

Suyao Jiang, Xuancheng Peng, Huanyu Zhou, Dazhao Zhang, Xi Liang, Danhua Cao, Zhenyu Yang, and Ming Zhao*
Author Affiliations
  • School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, Hubei , China
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    Figures & Tables(11)
    Imaging results of each channel camera under strong light scenarios compared with ground truth. (a) Visible RGB and visible polarization channels; (b) NIR channel; (c) LWIR channel
    Imaging quality comparison of multi-channel cameras in strong light scenarios. (a1)‒(a6) Color of oil spill is similar to that of water; (b1)‒(b6) oil spills have thickness differences
    Imaging results of each channel camera under low light scenarios compared with ground truth. (a) Visible RGB and visible polarization channels; (b) NIR channel; (c) LWIR channel
    Imaging quality comparison of multi-channel cameras in low light scenarios. (a1)‒(a6) With radiator interference on the water surface; (b1)‒(b6) without interference on the water surface
    Imaging results of each channel camera under sun glint scenarios compared with ground truth. (a) Visible RGB and visible polarization channels; (b) NIR channel; (c) LWIR channel
    Imaging quality comparison of multi-channel cameras in sun glint scenarios. (a1)‒(a6) Observation results of oil spills in overexposed areas near sun glint; (b1)‒(b6) observation results of large-area spotted sun glint on the water surface
    Information entropy comparison of cameras across channels in various scenarios
    Strong edge width comparison of cameras across channels in various scenarios
    • Table 1. Information entropy and strong edge width assessment of oil spill images in strong light scenarios

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      Table 1. Information entropy and strong edge width assessment of oil spill images in strong light scenarios

      Type of imageRGBS0ηDoLPθAoPLWIRNIR
      H /bitHA5.095.376.756.514.226.02
      HB5.565.897.006.424.577.07
      G /pixelGA17141191310
      GB121279115
    • Table 2. Information entropy and strong edge width assessment of oil spill images in low light scenarios

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      Table 2. Information entropy and strong edge width assessment of oil spill images in low light scenarios

      Type of imageRGBS0ηDoLPθAoPLWIRNIR
      H /bitHA3.674.547.066.864.064.65
      HB3.604.166.736.023.294.01
      G /pixelGA13109111716
      GB161610111413
    • Table 3. Information entropy and strong edge width assessment of oil spill images in sun glint scenarios

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      Table 3. Information entropy and strong edge width assessment of oil spill images in sun glint scenarios

      Type of imageRGBS0ηDoLPθAoPLWIRNIR
      H /bitHA6.406.266.794.494.597.29
      HB5.765.956.925.454.837.33
      G /pixelGA1110913159
      GB810817177
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    Suyao Jiang, Xuancheng Peng, Huanyu Zhou, Dazhao Zhang, Xi Liang, Danhua Cao, Zhenyu Yang, Ming Zhao. Oil Spill Detection Methods on Water Surface Based on Multi-Dimension Optical Remote Sensing Imaging[J]. Acta Optica Sinica (Online), 2025, 2(15): 1514002

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    Paper Information

    Category: Applied Optics and Optical Instruments

    Received: Jun. 20, 2025

    Accepted: Jul. 7, 2025

    Published Online: Aug. 7, 2025

    The Author Email: Ming Zhao (zhaoming@hust.edu.cn)

    DOI:10.3788/AOSOL250482

    CSTR:32394.14.AOSOL250482

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