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Utilisation of Contour Criteria in Micro-Segmentation of SAR Images

机译:轮廓准则在SAR图像微分割中的应用

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The hierarchical segmentation of SAR (Synthetic Aperture Radar) images is greatly complicated by the presence of coherent speckle. We are exploring the utilisation of spatial constraints and contour shapes in order to improve the segmentation results. With standard merging criterion, the high noise level of SAR images results in the production of micro-regions that have variable mean and variance values and irregular shapes. If the micro-segments are not correctly delimited then the following steps will merge segments from different fields. In examining the evolution of the initial segments, we see that the merging should take into account spatial aspects. Particularly, the segment contours should have good shapes. We present three criteria based upon contour shapes.
机译:由于存在相干斑点,SAR(合成孔径雷达)图像的分层分割变得非常复杂。我们正在探索利用空间约束和轮廓形状来改善分割结果。按照标准的合并标准,SAR图像的高噪声水平会导致产生具有均值和方差值可变且形状不规则的微区域。如果微段未正确定界,则以下步骤将合并来自不同字段的段。在检查初始段的演变时,我们看到合并应该考虑到空间方面。特别地,段轮廓应该具有良好的形状。我们提出了基于轮廓形状的三个标准。

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