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Object-oriented change detection of multi-polarization SAR images based on unitemporal image segmentation

机译:基于单时空图像分割的多极化SAR图像面向对象变化检测

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Object-oriented change detection is to detect change by comparing the features of image objects. Its key is how to describe the images at two temporal phases with the same segmentation boundries in order to realize the one to one comparision between the two sets of segments from two different images. In this paper, the authors put forward a novel change detection method based on unitemporal image segmentation. This method can well address this problem even without the GIS auxiliary data, and performance well in the change detection of fully polarimetric SAR images.
机译:面向对象的变化检测是通过比较图像对象的特征来检测变化。其关键是如何在具有相同分割边界的两个时间相位上描述图像,以实现来自两个不同图像的两组片段之间的一对一比较。本文提出了一种基于单时空图像分割的变化检测新方法。即使没有GIS辅助数据,该方法也可以很好地解决此问题,并且在全极化SAR图像的变化检测中性能良好。

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