An Optical-to-SAR Transformation Method for SAR Ship Image Augmentation

Ke-Jian Li, Shenshen Luan, Dong Zhou
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Abstract

For ship detection in remote sensing, the labeled synthetic aperture radar (SAR) ship images are far less than optical ship images, which limited the development of SAR ship detection and classification. In this paper, an optical-to-SAR transformation method is proposed to transforming the well labeled optical ship images to SAR ship images. Based on electromagnetic theory, the backscattering and reflection mechanism is analyzed and modeled into the transformation. A background iteration method based on probability theory is also proposed to learn the distribution of SAR ship images. The result shows that the proposed method can transform the optical ship images to SAR ship images with the confidence coefficient of 84.643%.
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舰船SAR图像增强的光学-SAR变换方法
在遥感船舶检测中,标记合成孔径雷达(SAR)舰船图像远不如光学舰船图像,限制了SAR舰船检测与分类的发展。本文提出了一种将标记好的光学舰船图像转换为SAR舰船图像的方法。基于电磁学理论,分析了后向散射和反射机理,并将其模型化。提出了一种基于概率论的背景迭代方法来学习SAR舰船图像的分布。结果表明,该方法可将光学舰船图像转换为SAR舰船图像,置信系数为84.643%。
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