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基于面向对象和模糊逻辑的SAR溢油检测算法

苏腾飞 李永香 李洪玉

苏腾飞, 李永香, 李洪玉. 基于面向对象和模糊逻辑的SAR溢油检测算法[J]. 海洋学报, 2016, 38(1): 69-81. doi: 10.3969/j.issn.0253-4193.2016.01.007
引用本文: 苏腾飞, 李永香, 李洪玉. 基于面向对象和模糊逻辑的SAR溢油检测算法[J]. 海洋学报, 2016, 38(1): 69-81. doi: 10.3969/j.issn.0253-4193.2016.01.007
Su Tengfei, Li Yongxiang, Li Hongyu. Sea oil spill detection method by SAR imagery using object-based image analysis and fuzzy logic[J]. Haiyang Xuebao, 2016, 38(1): 69-81. doi: 10.3969/j.issn.0253-4193.2016.01.007
Citation: Su Tengfei, Li Yongxiang, Li Hongyu. Sea oil spill detection method by SAR imagery using object-based image analysis and fuzzy logic[J]. Haiyang Xuebao, 2016, 38(1): 69-81. doi: 10.3969/j.issn.0253-4193.2016.01.007

基于面向对象和模糊逻辑的SAR溢油检测算法

doi: 10.3969/j.issn.0253-4193.2016.01.007
基金项目: 国家自然科学基金(60890075)。

Sea oil spill detection method by SAR imagery using object-based image analysis and fuzzy logic

  • 摘要: 星载合成孔径雷达(Synthetic Aperture Radar,SAR)具有全天时、全天候的工作能力,已被众多学者认为是非常适合探测海面溢油污染的遥感器。然而在SAR影像中经常出现"类油膜"现象,这严重干扰了SAR溢油检测的精度。因此,如何有效区分SAR影像中的油膜和类油膜,对提升溢油检测精度具有重要意义。本文利用面向对象图像分析的方法,从20景ENVISAT ASAR影像中提取了较多的溢油和类油膜样本,对其基于对象的形状、物理和纹理特征进行了综合分析,找出了适合区分溢油和类油膜的特征量。利用特征分析的结论,本文建立了一种基于模糊逻辑的溢油检测算法。该算法可以有效区分SAR影像中的溢油和类油膜,还可以给出暗斑被判定为溢油的概率。溢油检测实验说明,本文方法能够得到令人满意的效果。
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