Design of a testing method to assess the correctness of a point cloud colorization algorithm

The paper discusses a testing method for a point cloud colorization algorithm. The point cloud colorization process is described in the context of photogrammetric and laser scanning data integration. A parallel algorithm is described following a theoretical introduction to the problem of LiDAR data colorization. The paper consists of two main parts. The first part presents the testing methodology via two aspects: (1) correctness of the color assigned to a given point, (2) testing of interpolation methods. Both tests are used on synthetic and natural data, and the results are discussed. The second part consists of a discussion of correctness factors associated with point cloud colorization as a typical case of process correctness in data integration. Three important factors are discussed in the paper. The first is correctness of the external orientation of the given image. The second is the ratio of the density of the point cloud and the GSD of the image. The third is the relative angle between the image and the scanned plane. All of the results are presented in the paper and the optimal range of the relevant factors is also discussed.