为了提高面向对象分类的自动化程度,提出将分水岭变换与ISODATA聚类相结合对遥感影像进行面向对象分类。首先利用改进的分水岭变换对高分遥感影像进行分割,获得分割的对象后,利用ISODATA聚类方法对其进行分类。试验结果表明,该方法取得了较好的分类效果,且分类速度快,一定程度上提高了遥感影像分类的自动化。
In order to improve the automation of object-oriented classification,combines the watershed transform and ISODATA clustering to implement a quick and efficient object-oriented classification of remote sensing image. Firstly,uses the improved watershed transform to achieve better segmentation of high resolution imagery; then uses the ISODATA clustering to classify the object segmentation. The experimental results show that this new method obtains better classification effect and fast classification, and greatly enhances the automation of remote image classification.