面向对象的遥感影像单类分类

One-class classification of object-oriented remote sensing image

在遥感影像中只提取其中的一个特定类别,称为单类分类。结合面向对象分析方法,采用单类分类器提取影像中的兴趣类别。首先,探讨了面向对象遥感影像数据的分布特征和分割参数选择问题;然后,基于分割产生的影像对象,利用单类支持向量机方法,提取遥感影像中的特定类别信息。实验结果与基于像素的单类分类方法进行比较,表明结合面向对象的单类分类方法具有更高的分类精度。

One-class classification is to extract a specific class in remote sensing image. In combination with the objectoriented analysis method,the one-class classifier is used to extract the interest class from the remote sensing image. The distribution characteristics of object-oriented remote sensing image data and segmentation parameter selection are discussed. And then,on the basis of image object generated from segmentation,the method of one-class support vector machine is used to extract the specific classification information in remote sensing image. The result of object-oriented one-class classification method is compared with the experimental result,it shows that the object-oriented one-class classification method has higher classification accuracy.