Airborne LiDAR Data And Image Registration In Geophysical Prospecting Mode

Aerial geophysical prospecting (AGP) is an important method in the field of geophysical prospecting. Comparing with the traditional methods, AGP is much faster and more efficient with less labor force. It has become an important means of mineral resources exploration, making a significant contribution to national economic development. AGP aims at acquiring the geophysical information other than the topographical information and texture information of the ground surface, it motivates the idea of integrating aerial remote sensing into AGP. In this way, we can also get the corresponding aerial images, accurate height information and real-time attitude parameters which can serve as a reference for gravity terrain correction, geophysical anomaly elimination and gravity/magnetic parameters locating, etc. The enhancement of the accuracy and efficiency indicates the promising application prospect of this integrated system.Due to the big difference between the flight mode in AGP and traditional aerial remote sensing, however, the data processing becomes a big problem, especially the registration of aerial images and LiDAR points. In this paper, an automatic registration plan is introduced to solve this problem, considering the characteristics of AGP. First, it uses the correction parameters calculated by LiDAR system calibration to rectify the LiDAR point cloud. Second, it performs dense matching in each stereo pair, and carries out the registration procedure using ICP algorithm with the resulting matching point cloud and the LiDAR point cloud. Finally, it gives out the eccentric angle and eccentric component between the camera and the laser scanner. The major work and innovation are summarized as follows:(1) Rigorous equation of airborne LiDAR positioning is derived.This paper describes the components of LiDAR system as well as their working principle. It also presents the coordinate systems and coordinates transformation methods used in LiDAR system. On this basis, rigorous equation of airborne LiDAR positioning is given, and the system errors are analyzed.(2) An automatic LiDAR system error calibration method based on virtual connection point model is proposed.Comprehensive analysis of the existing LiDAR system error calibration methods is given, to achieve a coplanar-constraint-based LiDAR system calibration. As the corresponding planes are difficult for extraction and matching automatically, this paper presents a virtual connection point model, solving the correspondence problem between the discrete laser point clouds. Based on this model, a design is proposed of automatic LiDAR system error calibration.(3) A topological constraints strengthened stereo matching method based on least squares propagation is proposed.This paper discusses the existing stereo matching algorithms and the various constraints commonly used in stereo matching, then gives out a multi-constraint stereo matching algorithm. This algorithm strengthens rigid topological constraints to get the reliable matching seeds that are used for least squares propagation to overcome the effects of topography, improving the reliability of stereo matching.(4) designed an effective method for registration of image matching points with LiDAR pointsICP algorithm is selected for registration of image matching points and LiDAR points. Taken into account the differences between the two point clouds, this paper presents a preprocessing program for image matching points and LiDAR points respectively, which greatly enhances the accuracy of the corresponding points under ICP framework.(5) designed a quadtree indexing method for massive discrete point cloudSince the ICP algorithm requires repeated iterative process to determine the nearest point, it involves large amounts of data search and location operations. As LiDAR point cloud is unstructured, the efficiency is very low of random search in massive LiDAR point cloud. The proposed quadtree indexing method effectively raises the efficiency to find the nearest point.(6) proposed a registration model of stereo pair and LiDAR point cloud based on camera eccentric angle and eccentric componentAs camera and laser scanner are tightly connected in Leica ALS50 system, sharing one set of POS data, the major deviation between images and LiDAR data can be seen as the eccentric angle and eccentric component between camera and laser scanner. This paper presents a registration model based on camera eccentric angle and eccentric component. This model reduces the number of unknowns, so that all the stereo pairs can be rectified using a unified system error correction.