Accidental oil spills cause serious pollution to the ocean and are difficult to control in short time. It is an important guarantee for emergency disposal to effectively monitor oil spills. Remote sensing is the main means to monitor oil spills. High false alarm rate has been an important bottleneck of this technology. In this paper, a multi-time-domain shipborne radar images discrimination mechanism was proposed. Based on the improved Sobel operator, Otsu and linear interpolation, the co-frequency interference noises were detected and suppressed. Gray intensity correction model (GICM) and dual-threshold method were used to eliminate highlighted continuous pixels. Oil films were extracted by using an active contour model (ACM). Finally, a multi-time-domain discrimination mechanism based on variation range tolerance of identified oil films centroids was designed to reduce the false alarm rate. It can provide technical support for decision-making and emergency response.

中文翻译：

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基于主动轮廓模型的多时域舰载雷达图像漏油识别

意外的漏油事件会严重污染海洋，并且很难在短时间内加以控制。有效监控漏油是紧急处置的重要保证。遥感是监测溢油的主要手段。高误报率一直是该技术的重要瓶颈。提出了一种多时域舰载雷达图像识别机制。基于改进的Sobel算子，Otsu和线性插值，检测并抑制了同频干扰噪声。使用灰度强度校正模型（GICM）和双阈值方法消除突出显示的连续像素。通过使用主动轮廓模型（ACM）提取油膜。最后，设计了一种基于已识别油膜质心变化范围公差的多时域判别机制，以降低误报率。它可以为决策和紧急响应提供技术支持。