基于多特征的遥感影像分类方法

Classification of Remotely Sensed Imagery Using Multi-features Based Approach

提出了一种基于多特征的遥感分类方法。首先 ,制定类方案并分解各个类 ,据此得到相应的子类 ;然后 ,通过选用适当的特征 ,使得每一个类都能以一个独特的特征组合来表达。与此同时 ,通过影像分割得到影像对象 ,并测量这些对象的各个特征 ,如光谱特征、几何特征及拓扑特征等。凭借这些特征 ,影像对象可以较为容易地被识别和分类。与传统的分类方法的比较表明 ,文中所提出的分类方法具有明显的优越性和良好的前景。

In this paper, a new method, namely the multi feature based method, was presented to classify remotely sensed imagery. A class scheme was firstly defined, in which, every class was decomposed into subclasses if necessary. Then, some suitable features were selected, and every subclass was characterized with a unique combination of these features. Meanwhile, the whole imagery was segmented into image objects, and subsequently the features used were measured, like spectral, geometrical and topological features. Using these features, image objects could be recognized and classified easily. By using the multi features based classification approach, classification accuracy was improved, and the classification results were easier interpreted when compared with the conventional classification method.