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Level sets with one dot fuzzy initialization for marine oil spill segmentation

机译:水平集和一点模糊初始化,用于海洋溢油分割

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Image segmentation techniques are widely used for identifying marine oil spill regions in SAR images, with one representative technique being level set evolution. The accuracy of level set evolution highly relies on a proper initial level set function which roughly captures the marine oil spill layouts in a SAR image. However, marine oil spill regions are always complicatedly shaped, and it is time-consuming and impractical to manually devise precise initial level set functions for various marine oil spill shapes. In order to address this problem and achieve efficient and robust segmentation, we develop a one dot initialization scheme for level set evolution. Our method just requires an arbitrary pixel within one marine oil spill region as initialization. It exploits fuzzy connectedness between pixels such that consistent initial level set functions can be established via arbitrary initial dots within the marine oil spill region. Experimental results validates the robustness of our strategy.
机译:图像分割技术被广泛用于识别SAR图像中的海上溢油区域,其中一种代表性的技术是水平集演化。水平集演变的准确性高度依赖于适当的初始水平集功能,该功能可以大致捕获SAR图像中的海上溢油布局。然而,海洋溢油区域的形状总是复杂的,并且为各种海洋溢油形状手动设计精确的初始水平设定功能是耗时且不切实际的。为了解决此问题并实现有效且鲁棒的分割,我们开发了一种用于点集演化的单点初始化方案。我们的方法只需要在一个海洋溢油区域内的任意像素作为初始化。它利用像素之间的模糊连接性,从而可以通过海洋溢油区域内的任意初始点建立一致的初始水平集功能。实验结果验证了我们策略的稳健性。

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