Sea surface oil spill identification method based on SAR polarization ratio and texture feature

Chen Han; Xie Tao; Fang He; Meng Lei; Zhao Li; Ai Runbing

doi:10.3969/j.issn.0253-4193.2019.09.017

Volume 41 Issue 9

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Chen Han，Xie Tao，Fang He, et al. Sea surface oil spill identification method based on SAR polarization ratio and texture feature[J]. Haiyang Xuebao，2019, 41(9)：181–190，doi:10.3969/j.issn.0253−4193.2019.09.017

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Sea surface oil spill identification method based on SAR polarization ratio and texture feature

doi: 10.3969/j.issn.0253-4193.2019.09.017

Chen Han^1
,,
Xie Tao^{2, 3
,
,},
Fang He¹,
Meng Lei⁴,
Zhao Li¹,
Ai Runbing¹

1.
School of Marine Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
3.
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
4.
Beijing City 5111 Mailbox, Beijing 100094, China

Received Date: 2018-09-08
Rev Recd Date: 2018-11-25

Available Online: 2021-04-21

Publish Date: 2019-09-25

Abstract

Abstract

Aiming at the characteristics of SAR images on the ocean surface, the texture feature method based on gray level co-occurrence matrix is a common method for extracting oil spill information from the sea surface, but the complex information on the actual ocean surface makes the SAR image produce a dark spot area similar to the oil spill phenomenon. The false alarm rate is obtained when the oil feature information is extracted by the texture feature method, and the extraction precision of the oil spill information is reduced. Based on the RADARSAT-2 SAR quadratic polarization image, this paper proposes a texture feature recognition method based on SAR polarization ratio image to identify and extract the oil film on the sea surface. The results show that the texture feature recognition method based on SAR polarization ratio image can effectively and accurately extract the oil spill information on the sea surface. Compared with the texture feature recognition method of VV polarization image, the false alarm rate in the oil spill monitoring process is reduced by 17.96 %, the overall accuracy of oil spill monitoring reached 96.83%.
- synthetic aperture radar,
- oil spill identification,
- polarization ratio,
- texture feature

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References(25)

References

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