Journal of the Indian Society of Remote Sensing

, Volume 46, Issue 12, pp 1949–1961 | Cite as

Marine Radar Oil Spill Monitoring Technology Based on Dual-Threshold and C–V Level Set Methods

  • Jin XuEmail author
  • Peng Liu
  • Haixia Wang
  • Jingjing Lian
  • Bo Li
Research Article


Marine radar oil spill monitoring technology has the advantages of wide-range target detection, a flexible working mode, and the ability to operate in severe weather. Based on oil spill data collected from the 7.16 accident in Dalian, China, two comprehensive oil spill monitoring methods using X-band horizontal polarized marine radar are presented. The improved Prewitt operator, Otsu algorithm, median filtering, and mean filtering were used to preprocess the original marine radar image. Subsequently, the recognition of offshore oil films were studied via the dual-threshold method and C–V level set method. Results show that the image data achieved the ideal noise reduction effect after pretreatment, and retained marine radar ocean wave information effectively. The C–V level set method required relatively lower levels of data preprocessing. However, it relied heavily on the energy-driven window by expert presupposition. It was therefore only suitable for obtaining continuous oil film information. Its calculation efficiency was related to the number of evolutions and the size of the image. The dual-threshold method required higher data preprocessing. Furthermore, the effective monitoring range of ocean waves must be determined in advance. This method could identify discrete oil film information at sea and had high computational efficiency. The dual-threshold method is better for the automatic identification of marine oil film information. The two kinds of monitoring methods described herein are useful for the identification and disposal of oil spills at sea.


Oil spill Marine remote sensing Dual-threshold method C–V level set method Image processing X-band marine radar 



Funding was provided by National Natural Science Foundation of China (Grant No. 51709031), Fundamental Research Funds for the Central Universities (Grant No. 3132016003) and Doctoral Scientific Research Foundation of Liaoning Province (Grant No. 201601069).


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Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  • Jin Xu
    • 1
    Email author
  • Peng Liu
    • 1
  • Haixia Wang
    • 1
  • Jingjing Lian
    • 1
  • Bo Li
    • 2
  1. 1.Navigation CollegeDalian Maritime UniversityDalianChina
  2. 2.Laboratory DepartmentLiaoning Reconnaissance Institute of Hydrogeology and Engineering GeologyDalianChina

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