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SEA OIL SPILL DETECTION USING SELF-SIMILARITY PARAMETER OF POLARIMETRIC SAR DATA

机译:极化SAR数据自相似参数的海油泄漏检测

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The ocean oil spills cause serious damage to the marine ecosystem. Polarimetric Synthetic Aperture Radar (SAR) is an important mean for oil spill detections on sea surface. The major challenge is how to distinguish oil slicks from look-alikes effectively. In this paper, a new parameter called self-similarity parameter, which is sensitive to the scattering mechanism of oil slicks, is introduced to identify oil slicks and reduce false alarm caused by look-alikes. Self-similarity parameter is small in oil slicks region and it is large in sea region or look-alikes region. So, this parameter can be used to detect oil slicks from look-alikes and water. In addition, evaluations and comparisons were conducted with one Radarsat-2 image and two SIR-C images. The experimental results demonstrate the effectiveness of the self-similarity parameter for oil spill detection.
机译:海洋石油泄漏严重损害了海洋生态系统。极化合成孔径雷达(SAR)是检测海面溢油的重要手段。主要挑战是如何有效区分浮油和外观。在本文中,引入了一个新的自相似参数,该参数对浮油的散射机制很敏感,可以识别浮油并减少由相似现象引起的误报。自相似参数在浮油区较小,在海区或相似区较大。因此,此参数可用于从外观和水中检测浮油。此外,对一张Radarsat-2图像和两张SIR-C图像进行了评估和比较。实验结果证明了自相似参数对漏油检测的有效性。

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