Object-Based Fusion and Classification of Airborne Laser Scanning Data and Aerial Images

We propose a new object-based fusing and classification approach of combination of airborne laser scanning data and aerial images.Firstly,a image segmentation,based on spliting and merging with pyramid data,can be processed on aerial image to get a set of disjoint regions.Then,to every region,filtering results,height difference information and sparse character of airborne laser scanning data and line segments,which is extracted from aerial image,can be investigated to classify this region to a kind class.Experiment results show that this method can divide point clouds to three fundamental objects efficiently and reliably.