Abstract
Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.
Highlights
Nowadays, Light Detection and Ranging (LiDAR ) system can get high accuracy height information rapidly, LiDAR data is lack of semantic information compared to images which have higher precision plane accuracy and rich texture information (Baltsavias, 1999)
The workflow of airborne LiDAR point cloud data and synchronous digital image co-registration based on combined adjustment is shown in Figure. 1, it is composed of 3 steps
The elevation of tie point object coordinates calculated by forward spatial intersection via collinearity equation will close to the DSM elevation interpolated by LiDAR point cloud, when the EOPs provided by POS system do not contain errors
Summary
Light Detection and Ranging (LiDAR ) system can get high accuracy height information rapidly, LiDAR data is lack of semantic information compared to images which have higher precision plane accuracy and rich texture information (Baltsavias, 1999). Existing methods can be roughly divided into two categories: one kind is the direct registration method based on feature matching (González-Aguilera et al, 2009; Renaudin et al, 2011); the other is by generating 3D point cloud from images, and register two types of point cloud by Iterative Closest Points method (Zhao et al, 2005; Habib et al, 2006) The former one depends on automatic feature matching, which is still a difficult problem; the latter one is less efficiency due to the time-consuming photogrammetry processing for producing 3D point cloud. Aim at the above problems, this paper proposed a method of co-registration airborne laser point cloud data with the synchronous digital image, which dose consider the placement angle error of POS system, and consider the GPS offset
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