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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Automatic Extraction of Offshore Platforms in Single SAR Images Based on a Dual-Step-Modified Model
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Automatic Extraction of Offshore Platforms in Single SAR Images Based on a Dual-Step-Modified Model

机译：基于双步修正模型的单SAR图像中海洋平台自动提取

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摘要

The quantity and location of offshore platforms are of great significance for marine oil spill monitoring and offshore oil-gas development. In the past, multiphase medium- and low-resolution optical or radar images have been used to remove the interference of ship targets based on the static position of a platform to extract the offshore platform, resulting in large demands and high image data costs. According to the difference in shape between offshore platforms (not elongated) and ships (elongated shapes) in SAR (synthetic aperture radar) images, this paper proposes an automatic extraction method for offshore platforms in single SAR images based on a dual-step-modified model. First, the two-parameter CFAR (constant false alarm rate) algorithm was used to detect the possible offshore platform targets; then, the Hough transform was introduced to detect and eliminate ship targets with linear structures. Finally, the final offshore platform was obtained. Experiments were carried out in four study areas in the Beibu Gulf basin and the Pearl River estuary basin in the northern South China Sea. The results show that the method has a good extraction effect in the above research area, and the extraction accuracy rate of offshore platforms is 86.75%. A single SAR image can obtain satisfactory extraction results, which greatly saves on image data cost.
机译：海上平台的数量和位置对于海上溢油监测和海上油气开发具有重要意义。过去，基于平台的静态位置来提取海上平台，多相中低分辨率光学或雷达图像已被用于消除舰船目标的干扰，导致需求量大和图像数据成本高。针对合成孔径雷达图像中海上平台（非拉长型）与舰船（细长形状）的形状差异，提出了一种基于双步修正的单SAR图像中海上平台自动提取方法。模型。首先，使用两参数CFAR（恒定误报率）算法检测可能的海上平台目标；然后，引入了霍夫变换来检测和消除具有线性结构的舰船目标。最终，获得了最终的海上平台。在南海北部北部湾盆地和珠江口盆地的四个研究区域进行了实验。结果表明，该方法在上述研究领域具有良好的提取效果，海上平台的提取准确率为86.75％。单个SAR图像可以获得令人满意的提取结果，大大节省了图像数据成本。

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