Oil spill detection on X-band marine radar images based on sea clutter fitting model

被引:0
|
作者
Liu, Peng [1 ]
Liu, Bingxin [1 ]
Li, Ying [2 ]
Chen, Peng [1 ]
Xu, Jin [3 ]
机构
[1] Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China
[2] Dalian Maritime Univ, Environm Informat Inst, Dalian 116026, Peoples R China
[3] Guangdong Ocean Univ, Maritime Coll, Zhanjiang 524088, Peoples R China
基金
中国国家自然科学基金;
关键词
X-band marine radar; Radar images; Oil spill detection; Sea clutter fitting; EXTRACTION;
D O I
10.1016/j.heliyon.2023.e20893
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Oil spills could cause great harm to the natural environment. The ability to identify them accurately is critical for prompt response and treatment. We proposed a sea clutter fitting model of marine radar images for oil spill detection. The model is derived from the geometric structure of the marine radar, the expression of marine radar received power, and the rough surface scattering model of the sea surface. In the denoised marine radar image, the sea clutter fitting model is used to detect coarse oil spills. Then the fine measurement is carried out by mean filter, the Otsu method, and noise reduction. The proposed oil spill detection method was used on radar images sampled after an oil spill accident happened in a coastal region in Dalian, China, on July 21, 2010. The proposed method can detect oil spills without human intervention, and the extracted oil spills are accurate and consistent with visual interpretation.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Oil spill detection method using X-band marine radar imagery
    Zhu, Xueyuan
    Li, Ying
    Feng, Haiyang
    Liu, Bingxin
    Xu, Jin
    JOURNAL OF APPLIED REMOTE SENSING, 2015, 9
  • [2] Adaptive Enhancement of X-Band Marine Radar Imagery to Detect Oil Spill Segments
    Liu, Peng
    Li, Ying
    Xu, Jin
    Zhu, Xueyuan
    SENSORS, 2017, 17 (10)
  • [3] Semi-Automatic Oil Spill Detection on X-Band Marine Radar Images Using Texture Analysis, Machine Learning, and Adaptive Thresholding
    Liu, Peng
    Li, Ying
    Liu, Bingxin
    Chen, Peng
    Xu, Jin
    REMOTE SENSING, 2019, 11 (07)
  • [4] An improved algorithm for phase-resolved sea surface reconstruction from X-band marine radar images
    Zinchenko, Victoria
    Vasilyev, Leonid
    Halstensen, Svein Olav
    Liu, Yuming
    JOURNAL OF OCEAN ENGINEERING AND MARINE ENERGY, 2021, 7 (01) : 97 - 114
  • [5] An improved algorithm for phase-resolved sea surface reconstruction from X-band marine radar images
    Victoria Zinchenko
    Leonid Vasilyev
    Svein Olav Halstensen
    Yuming Liu
    Journal of Ocean Engineering and Marine Energy, 2021, 7 : 97 - 114
  • [6] Oil spill identification in X-band marine radar image using K-means and texture feature
    Chen, Rong
    Li, Bo
    Jia, Baozhu
    Xu, Jin
    Ma, Long
    Yang, Hongbo
    Wang, Haixia
    PEERJ COMPUTER SCIENCE, 2022, 8
  • [7] Rain Detection From X-Band Marine Radar Images: A Support Vector Machine-Based Approach
    Chen, Xinwei
    Huang, Weimin
    Zhao, Chen
    Tian, Yingwei
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 58 (03): : 2115 - 2123
  • [8] Estimation of Sea Surface Current from X-Band Marine Radar Images by Cross-Spectrum Analysis
    Chen, Zhongbiao
    Zhang, Biao
    Kudryavtsev, Vladimir
    He, Yijun
    Chu, Xiaoqing
    REMOTE SENSING, 2019, 11 (09)
  • [9] Clutter suppression and marine target detection for radar images based on INet
    Mou X.
    Chen X.
    Guan J.
    Zhou W.
    Liu N.
    Dong Y.
    Journal of Radars, 2020, 9 (04) : 640 - 653
  • [10] Wind Direction Extraction from X-Band Marine Radar Images Based on the Attenuation Horizontal Component
    Yu, Huanyu
    Lu, Zhizhong
    Wang, Hui
    REMOTE SENSING, 2023, 15 (16)