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Feature extraction and classification of ocean oil spill based on SAR image

机译:基于SAR图像的海洋溢油特征提取与分类

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摘要

The detection of ocean oil spill based on synthetic aperture radar (SAR) image has been a hot topic attracting extensive attention. In this paper, a hybrid scheme, in which we extract feature parameters and then achieve classification as follows, is presented. Two-dimensional (2-D) Otsu algorithm is applied in image segmentation process, and neural network is applied in classification course. Before image segmentation, a sort of universal processing is used, and it enables 2-D Otsu algorithm to be more applicable to SAR images of ocean oil spill.
机译:基于合成孔径雷达(SAR)图像的海洋溢油检测一直是引起广泛关注的热点。本文提出了一种混合方案,其中我们提取特征参数,然后实现如下分类。二维(2-D)Otsu算法应用于图像分割过程,神经网络应用于分类过程。在图像分割之前,使用了一种通用处理方法,它使二维Otsu算法更适用于海洋溢油的SAR图像。

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