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Semantic segmentation of polarimetric SAR image via the uniform homogeneity slice

机译:均匀均匀切片对极化SAR图像的语义分割

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PolSAR image segmentation has long been an important problem in the PolSAR remote sensing community. Many segmentation algorithms describe images in terms of a hierarchy of regions. However, it is often over-segmentation at finer levels and under-segmentation at coarser levels, which makes it difficult to adopt the hierarchies for later use. In this paper, we propose an effective measure to extract a single segmentation from the hierarchical structures of PolSAR images. We call our method the uniform homogeneity slice, which select a set of regions that balance the homogeneity from the hierarchy. First, we construct the Binary partition tree (BPT) which is a multi-scale image representation to obtain a hierarchy of regions. Once the tree has been constructed, we use the uniform homogeneity slice to prune the tree and filter the complex hierarchies into a single segmentation. Experimental results on NASA/JPL AIRSAR and DLR E-SAR images demonstrate the effectiveness of the proposed approach.
机译:长期以来,PolSAR图像分割一直是PolSAR遥感界的重要问题。许多分割算法根据区域的层次来描述图像。但是,它通常在较细的级别上过度分割,而在较粗的级别上分割不足,这使得很难采用该层次结构以备后用。在本文中,我们提出了一种有效的措施,可以从PolSAR图像的层次结构中提取单个分割。我们将我们的方法称为统一同质切片,该切片从层次结构中选择一组平衡同质的区域。首先,我们构建二进制分区树(BPT),它是一种多尺度图像表示形式,用于获取区域层次结构。构造完树后,我们使用统一的均匀性切片对树进行修剪,并将复杂的层次结构过滤到单个分段中。在NASA / JPL AIRSAR和DLR E-SAR图像上的实验结果证明了该方法的有效性。

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