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Wiener filter-based change detection for SAR imagery

机译：基于维纳滤波器的SAR图像变化检测

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摘要

In this paper we propose a Wiener filter-based change detection algorithm for the detection of mines in Synthetic Aperture Radar (SAR) imagery. By computing second order statistics, the Wiener filter-based method has demonstrated improved performance over Euclidean distance. It is more robust to the presence of highly correlated speckle noise, misregistration errors, and nonlinear variations in the two SAR scenes. These variations may result from differences in the data acquisition systems and varying conditions during the different data collect times. A method very similar to the Mahalanobis distance was also implemented to detect mines in SAR images and has shown similar performance to the Wiener filter-based method. We present results in the form of receiver operating characteristics (ROC) curves, comparing simple Euclidean difference change detection, Mahalanobis difference-based change detection, and the proposed Wiener filter-based change detection in both global and local implementations.
机译：在本文中，我们提出了一种基于维纳滤波器的变化检测算法，用于在合成孔径雷达（SAR）图像中检测地雷。通过计算二阶统计量，基于维纳滤波器的方法已证明在欧几里得距离上具有改进的性能。对于两个SAR场景中存在高度相关的斑点噪声，配准错误和非线性变化，它更健壮。这些变化可能是由于数据采集系统的差异以及在不同数据收集时间期间条件的变化所导致的。还实现了一种与马哈拉诺比斯距离非常相似的方法来检测SAR图像中的地雷，并且其性能与基于Wiener滤波器的方法相似。我们以接收器工作特性（ROC）曲线的形式呈现结果，在全局和本地实现中比较简单的欧几里德差异检测，基于Mahalanobis差异检测和建议的基于Wiener滤波器的变更检测。

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