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Remote Sensing
Volume 17
Issue 18
10.3390/rs17183148
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Oil Spill Identification with Marine Radar Using Feature Augmentation and Improved Firefly Optimization Algorithm

by
Jin Xu
1,2,3,4,
Boxi Yao
1,2,
Haihui Dong
1,2,3,4,*,
Zekun Guo
1,2,
Bo Xu
1,2,
Yuanyuan Huang
1,2,
Bo Li
1,2,3,4,
Sihan Qian
1,2 and
Bingxin Liu
5
1
Shenzhen Institute of Guangdong Ocean University, Shenzhen 518116, China
2
Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524091, China
3
Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province, Zhanjiang 524088, China
4
Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Guangdong Ocean University, Zhanjiang 524088, China
5
Navigation College, Dalian Maritime University, Dalian 116026, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(18), 3148; https://doi.org/10.3390/rs17183148
Submission received: 23 July 2025 / Revised: 7 September 2025 / Accepted: 9 September 2025 / Published: 10 September 2025
Versions Notes

Abstract

Oil spill accidents pose a grave threat to marine ecosystems, human economy, and public health. Consequently, expeditious and efficacious oil spill detection technology is imperative for the pollution mitigation and the health preservation in the marine environment. This study proposed a marine radar oil spill detection method based on Local Binary Patterns (LBP), Histogram of Oriented Gradient (HOG), and an improved Firefly Optimization Algorithm (IFA). In the stage of image pre-processing, the oil film features were significantly enhanced through three steps. The LBP features were extracted from the preprocessed image. Then, the mean filtering was used to smooth out the LBP features. Subsequently, the HOG statistical features were extracted from the filtered LBP feature map. After the feature enhancement, the oil spill regions were accurately extracted by using K-Means clustering algorithm. Next, an IFA model was used to classify oil films. Compared with traditional Firefly Optimization Algorithm (FA) algorithm, the IFA method is suitable for oil film segmentation tasks in marine radar data. The proposed method can achieve accuracy segmentation and provide a new technical path for marine oil spill monitoring.
Keywords: oil spill; marine radar; LBP; HOG; K-means; Firefly Optimization Algorithm oil spill; marine radar; LBP; HOG; K-means; Firefly Optimization Algorithm

Share and Cite

MDPI and ACS Style

Xu, J.; Yao, B.; Dong, H.; Guo, Z.; Xu, B.; Huang, Y.; Li, B.; Qian, S.; Liu, B. Oil Spill Identification with Marine Radar Using Feature Augmentation and Improved Firefly Optimization Algorithm. Remote Sens. 2025, 17, 3148. https://doi.org/10.3390/rs17183148

AMA Style

Xu J, Yao B, Dong H, Guo Z, Xu B, Huang Y, Li B, Qian S, Liu B. Oil Spill Identification with Marine Radar Using Feature Augmentation and Improved Firefly Optimization Algorithm. Remote Sensing. 2025; 17(18):3148. https://doi.org/10.3390/rs17183148

Chicago/Turabian Style

Xu, Jin, Boxi Yao, Haihui Dong, Zekun Guo, Bo Xu, Yuanyuan Huang, Bo Li, Sihan Qian, and Bingxin Liu. 2025. "Oil Spill Identification with Marine Radar Using Feature Augmentation and Improved Firefly Optimization Algorithm" Remote Sensing 17, no. 18: 3148. https://doi.org/10.3390/rs17183148

APA Style

Xu, J., Yao, B., Dong, H., Guo, Z., Xu, B., Huang, Y., Li, B., Qian, S., & Liu, B. (2025). Oil Spill Identification with Marine Radar Using Feature Augmentation and Improved Firefly Optimization Algorithm. Remote Sensing, 17(18), 3148. https://doi.org/10.3390/rs17183148

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