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Change Detection Between SAR Images Using a Pointwise Approach and Graph Theory

机译：使用逐点方法和图论的SAR图像之间的变化检测

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摘要

This paper investigates the problem of change detection in multitemporal synthetic aperture radar (SAR) images. Our motivation is to avoid using a large-size dense neighborhood around each pixel to measure its change level, which is usually considered by classical methods in order to perform their accurate detectors. Therefore, we propose to develop a pointwise approach to detect land-cover changes between two SAR images employing the principle of signal processing on graphs. First, a set of characteristic points is extracted from one of the two images to capture the image's significant contextual information. A weighted graph is then constructed to encode the interaction among these keypoints and hence capture the local geometric structure of this first image. With regard to this graph, the coherence of the information carried by the two images is considered for measuring changes between them. In other words, the change level will depend on how much the second image still conforms to the graph structure constructed from the first image. Additionally, due to the presence of speckle noise in SAR imaging, the log-ratio operator will be exploited to perform the image comparison measure. Experimental results performed on real SAR images show the effectiveness of the proposed algorithm, in terms of detection performance and computational complexity, compared to classical methods.
机译：本文研究了多时相合成孔径雷达（SAR）图像中的变化检测问题。我们的动机是避免在每个像素周围使用大尺寸的密集邻域来测量其变化水平，这通常是经典方法为了执行其精确检测器所考虑的。因此，我们建议采用图上信号处理的原理，开发一种逐点方法来检测两个SAR图像之间的土地覆盖变化。首先，从两个图像之一中提取一组特征点，以捕获图像的重要上下文信息。然后构造一个加权图以对这些关键点之间的交互进行编码，从而捕获此第一张图像的局部几何结构。关于该图，考虑了两个图像所携带的信息的相干性以测量它们之间的变化。换句话说，变化水平将取决于第二图像仍然符合从第一图像构造的图结构的程度。另外，由于SAR成像中存在斑点噪声，因此将利用对数比运算符来执行图像比较措施。在实际SAR图像上进行的实验结果表明，与传统方法相比，该算法在检测性能和计算复杂度方面是有效的。

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