论文标题
非线性厨师距离用于异常变化检测
Nonlinear Cook distance for Anomalous Change Detection
论文作者
论文摘要
在这项工作中，我们提出了一种基于计时型方法的遥感图像中异常变化的方法。图像之间的回归器用于发现观察到的数据中最{\ em的影响点}。通常，残留最大的像素决定是异常的变化。为了找到异常的像素，我们考虑库克距离，并使用随机傅立叶特征作为有效的非线性撞击指标提出其非线性扩展。在不同的多光谱图像上显示了通过ROC曲线在视觉和定量评估的不同的多光谱图像上显示出良好的经验性能。
In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach. A regressor between images is used to discover the most {\em influential points} in the observed data. Typically, the pixels with largest residuals are decided to be anomalous changes. In order to find the anomalous pixels we consider the Cook distance and propose its nonlinear extension using random Fourier features as an efficient nonlinear measure of impact. Good empirical performance is shown over different multispectral images both visually and quantitatively evaluated with ROC curves.
