作　　者： ; ; ; ;

机构地区： 北京航空航天大学仪器科学与光电工程学院

出　　处： 《光学精密工程》 2009年第8期2004-2010,共7页

摘　　要： 正交子空间投影是一种需要已知待分类目标特征信息监督分类算法。为了扩展该算法的应用,本文提出了局部正交子空间投影算法,并将其成功应用于高光谱图像异常检测中。异常检测常用于自然背景下的人工目标提取,在小范围邻域内地物类型相对单一。基于此,以被检测点作为感兴趣目标,被检测点邻域内样本的均值作为不感兴趣目标,构造局部投影算子。实验结果显示:本算法能够检测出含量高于30%的亚像元目标;通过适当增大滑动窗尺寸,可检测像元面积较大的目标且不受Hughes效应影响;当波段数为80时,运算时间不足RX算法的1/10。得到的数据表明,局部正交子空间投影算法检测精度高、运算速度快,适用于实时高光谱图像异常检测。 The Orthogonal Subspace Projection （OSP） algorithm is a supervised classifier that needs the information of the classified objects. To expand its application, a local OSP （LOSP） is design to apply to detect the hyperspectral image. The anomaly detection algorithms are usually used to extract the isolated man-made objects in the nature background, where the substances in the small local region are usually uniform. Based on the principle, the LOSP is constructed by choosing the detected pixel as the interested object and the mean of its nearby pixels as the suppressed object. The experiments show that the LOSP can detect the sub-pixel targets with a content greater than 30%, and can also detect the targets occupying more pixels by enlarging the window size. In addition, LOSP is proved not to be affected by the Hughes phenomenon, and the computing time is less than 1/10 that by RX detector when the number of wavelengths is 80. LOSP is effective both in precision and in efficiency, and is applicable to the real-time detection of the hyperspectral image.

关 键 词： 遥感技术 高光谱图像 异常检测 正交子空间投影

领　　域： [自动化与计算机技术] [自动化与计算机技术]