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15 November 2023 An improved lightweight model for oil spill detection using dual-polarization SAR image
Dawei Wang, Shanwei Liu, Mingming Xu, Junfang Yang, Jianhua Wan
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Proceedings Volume 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023); 128150F (2023) https://doi.org/10.1117/12.3010241
Event: International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 2023, Kaifeng, China
Abstract
The increase in marine development and transportation has led to a rise in oil spills. SAR can operate in all-weather and all-time, which allows for continuous monitoring of the Earth’s surface. However, the challenges of insufficient feature extraction from SAR images and the require large amounts of memory to store the parameters and weights, cannot be overlooked. We propose an improved lightweight model that utilizes SqueezeNet as the encoder within the U-Net framework to address the aforementioned issues. And three polarization features were extracted from dual-polarization Sentinel-1 image. The experimental results show that our improved model achieves higher accuracy and dice than the other two models while also having a smaller size. The method provides novel ideas for real-time and accurate oil spill detection.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Dawei Wang, Shanwei Liu, Mingming Xu, Junfang Yang, and Jianhua Wan "An improved lightweight model for oil spill detection using dual-polarization SAR image", Proc. SPIE 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 128150F (15 November 2023); https://doi.org/10.1117/12.3010241
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KEYWORDS
Synthetic aperture radar
Polarization
Deep learning
Artificial intelligence
Electromagnetic scattering
Target detection
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