An improved building boundary extraction algorithm based on fusion of optical imagery and LIDAR data

Abstract This article presents a new method of automatic boundary extraction using LIDAR-optical fusion suited to handle diverse building shapes. This method makes full use of the complementary advantages of LIDAR data and optical imagery. Different building features are extracted from the two data sources and fused to form the final complete building boundaries. First, the points of each roof patch are detected from LIDAR point cloud. This process consists of four steps: filtering, building detection, wall point removal and roof patch detection. Second, initial building edges are extracted from optical imagery using an improved Canny detector constrained by edge location information derived from the LIDAR point cloud as edge buffer areas. Finally, the roof patch and initial edges are integrated by mathematical morphology to form the final complete building boundaries. All processes have no constraints or rules on building shapes. This method is fully data-driven and suitable for any building shape. LIDAR data and aerial images of complex geographical environments are used to test the method. These experimental results demonstrate that our method can automatically extract accurate boundaries for buildings with complex shapes, and also is highly robust in complex environments.