Research On Airborne LiDAR Points Cloud Data Filtering And LiDAR-Supported Image Matching

As an effective means of gathering and dealing with geospace information, the measuringtechnic using airborne LiDAR is a complementarity for traditional photogrammetry. AirborneLiDAR points cloud data filtering and LiDAR-supported image matching are mainly researchedin this thesis. On one hand, the correlative contents about points cloud data preprocessing andsome data filtering algorithms are researched; on the other hand, from the application aspect ofairborne LiDAR measuring technic, a LiDAR-supported image matching scheme is proposed.The finished works of this thesis are as follows:1. Airborne LiDAR points cloud data preprocessing is researched.4kinds of dataorganizing modes are compared, and the test results show that the most efficient method is byusing pseudo grid; then, an efficient method based on height frequence is researched to detect theoutliers, and the experimental results prove that this method could remove the outlierseffectively.2. On base of principle and deficiency of the original method, an improved hierarchicalmoving curved fitting filtering method is proposed using a strategy of filtrating lowest points,which is proved efficient to avoid filtering error when dealing with buildings of large size.3. A morphological filtering method based on fake scan lines is proposed. This methodarranges the original points like “Z” shape in row and column directions respectively, andfinishes the filtering process using morphological principle on base of the newly arranged points.Some experiments test the performance of this method and prove that it is more efficient than themethod based on pseudo grid.4. A LiDAR-supported image matching scheme is designed. Without troublesome searchingtactic, this method makes DSM which is generated by points cloud as guidance to obtain theinitial value for correlative coefficient matching. The experimental results show that this schemecould achieve image matching and prove the feasibility and validity of the guidance of airborneLiDAR points cloud data.