A classification method of building structures based on multi-feature fusion of UAV remote sensing images

Abstract

In order to improve the accuracy of building structure identification using remote sensing images, a building structure classification method based on multi-feature fusion of UAV remote sensing image is proposed in this paper. Three identification approaches of remote sensing images are integrated in this method: object-oriented, texture feature, and digital elevation based on DSM and DEM. So RGB threshold classification method is used to classify the identification results. The accuracy of building structure classification based on each feature and the multi-feature fusion are compared and analyzed. The results show that the building structure classification method is feasible and can accurately identify the structures in large-area remote sensing images.

Keywords

• Remote sensing image
• Building structure classification
• Multi-feature fusion
• Object-oriented classification method
• Texture feature classification method
• DSM and DEM elevation classification method