Object-Oriented Approach for ADS40 Image Classification

ADS40 images with high spatial resolution have many more spatial characteristics than low-resolution image except spectral characteristics.We introduced a object-oriented classification method based on multi-scale segmentation to classify ADS40 image of Taiyuan City.Firstly,the whole image is multi-scale segmented to get objects.Then,The features of objects,such as spectral,geometrical and topological characteristics,were measured.The hierarchical structure for classification was built.Finally,we applied a fuzzy rule classifier to extract the classification information of ADS40 images.The research shows that the object-oriented method can improve the overall classification accuracy of ADS40 images,reduce the Pepper and Salt' Pheomenon effectively,and meet the requirement of ADS40 images classification compared with classical classification approaches.