A STUDY ON ROOF POINT EXTRACTION BASED ON ROBUST ESTIMATION FROM AIRBORNE LIDAR DATA

Abstract

The airborne LIDAR scanning system is a whole new surveying technique that captures extremely detailed and abundant terrain surface information. Terrain information is implied in airborne LIDAR data.Roof points are especially important in airborne LIDAR data for 3-D building reconstruction. The key point for automatically and reliably extracting roof points from airborne LIDAR data is how to exclude irrelevant non-roof points. Robust estimation is a theory about how to remove blunders from observations. If the nonroof points are viewed as blunders, it is possible to develop an algorithm to acquire the roof points, based on robust estimation theory. This paper will therefore study how to develop an algorithm to acquire those roof LIDAR points and remove irrelevant non-roof LIDAR points, based on robust estimation theory. Problems relevant to the proposed algorithm will be investigated in this study through experiments in order to understand the feasibility of the proposed algorithm and to further develop an automatic algorithm to extract roof points from airborne LIDAR data.