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

Sun Xiaoxia, Z. JiXian, Y. Qin, Zhai Liang
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引用次数: 6

Abstract

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.
基于单时分割的多极化SAR图像面向对象变化检测
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。其关键是如何用相同的分割边界来描述两个时间阶段的图像,从而实现两幅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位时间图像分割的变化检测方法。该方法在没有GIS辅助数据的情况下也能很好地解决这一问题,在全极化SAR图像的变化检测中表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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