一种基于高斯马尔可夫随机场的异常目标探测方法

利用高斯马尔可夫随机场模型描述像元的邻域相关性信息,并将这种邻域信息引入到局域异常探测器中,提出了一种顾及邻域信息的高光谱遥感影像局域异常目标探测算法。实验证明,该方法克服了传统异常探测方法仅仅利用光谱信息的不足,比经典的RX算法的探测效果更好,并且可以更有效地探测出大于一个像元的异常目标。

An anomaly detection method based on gauss markov random field

This paper presented an anomaly detection method based on Gauss Markov Random Field model in order to introduce the spatial information between the neighborhood pixels in the hyperspectral imagery into the anomaly detection procedure.In this method,the neighborhood relationshi Pof the pixels in the hyperspectral imagery was described by the Gauss Markov Random Field (GMRF) model.Then this neighborhood relationshi Pinformation between pixels was introduced into the local-region anomaly detector which uses a nested dual window to detect probable anomaly pixels.Experiments showed that this method performs better than the traditional RX-algorithm,especially for the larger anomaly targets which usually contain several neighborhood pixels.