遥感图像像素级异常识别的一种方法  

A Method for Extracting Anomalous Pixels of Remotely Sensed Data

作　　者：陈永良[1] 李学斌[1] 林楠[1] 

机构地区：[1]吉林大学综合信息矿产预测研究所,长春130026

出　　处：《吉林大学学报（地球科学版）》2012年第3期881-886,共6页Journal of Jilin University：Earth Science Edition

基　　金：国家自然科学基金项目(40872193;41072244);国家自然科学基金重点项目(61133011)

摘　　要：遥感图像异常识别是遥感应用领域一个颇受关注的研究课题,在军事目标识别和自然环境保护等许多领域都有潜在应用价值。不妨假设遥感图像背景像素分布于随空间位置缓慢变化的一系列高斯超椭球体内,异常像素则分布于超椭球体之外。在这种假设前提下,首先应用Weiszfeld方法估算遥感图像中一系列高斯超椭球体的重心和波段协方差矩阵;然后,计算各像素到对应的超椭球体重心的马氏距离,并用直方图法确定马氏距离的异常下限;最后,把马氏距离高于异常下限的像素作为异常像素识别出来。在GDAL遥感图像数据输入输出函数库基础上,用VC++语言开发了遥感图像像素级异常识别的算法程序;用美国亚特兰大TM图像进行了方法的应用实验研究。结果表明,该方法对遥感图像中的局部异常具有很好的识别效果。Anomaly detection of remotely sensed data is one problem of the application research fields paid more attention to.It has potential applications in many fields such as military object recognition and environmental protection.Without loss of generality,it can be assumed that background pixels of remotely sensed data distribute within a series of space-varying hyper-ellipsoids while anomalous pixels locate out of those hyper-cubes.Holding on this hypothesis,the authors first apply Weiszfeld method to estimate the centers and cross-band covariances of these hyper-ellipsoids in remotely sensed data,then compute the Mahalanobis distance of each pixel to the center of the corresponding hyper-ellipsoid and determine the threshold using Mahalanobis histogram,finally,recognize the anomalous pixels of which the Mahalanobis distance is over the threshold.The authors develop a visual C＋＋ program for recognizing anomalous pixels from remotely sensed data on the basis of GDAL function library for input and output of remotely sensed data.The authors conduct an experimental application on the new methd using the TM image of Atlanda.The experimental results show that the method can properly recognize local anomalies in remotely sensed image data.

关 键 词：Weiszfeld方法 马氏距离 协方差矩阵 像素异常提取 遥感图像 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]