A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

Over the past few years, accurate 3D surface reconstruction using remotely-sensed data has been recognized as a prerequisite for different mapping, modelling, and monitoring applications. To fulfill the needs of these applications, necessary data are generally collected using various digital imaging systems. Among them, laser scanners have been acknowledged as a fast, accurate, and flexible technology for the acquisition of high density 3D spatial data. Despite their quick accessibility, the acquired 3D data using these systems does not provide semantic information about the nature of scanned surfaces. Hence, reliable processing techniques are employed to extract the required information for 3D surface reconstruction. Moreover, the extracted information from laser scanning data cannot be effectively utilized due to the lack of descriptive details. In order to provide a more realistic and accurate perception of the scanned scenes using laser scanning systems, a new approach for 3D reconstruction of planar surfaces is introduced in this paper. This approach aims to improve the interpretability of the extracted planar surfaces from laser scanning data using spectral information from overlapping imagery collected onboard modern low-cost aerial mapping systems, which are widely adopted nowadays. In this approach, the scanned planar surfaces using laser scanning systems are initially extracted through a novel segmentation procedure, and then textured using the acquired overlapping imagery. The implemented texturing technique, which intends to overcome the computational inefficiency of the previously-developed 3D reconstruction techniques, is performed in three steps. In the first step, the visibility of the extracted planar surfaces from laser scanning data within the collected images is investigated and a list of appropriate images for texturing each surface is established. Successively, an occlusion detection procedure is carried out to identify the occluded parts of these surfaces in the field of view of captured images. In the second step, visible/non-occluded parts of the planar surfaces are decomposed into segments that will be textured using individual images. Finally, a rendering procedure is accomplished to texture these parts using available images. Experimental results from overlapping laser scanning data and imagery collected onboard aerial mapping systems verify the feasibility of the proposed approach for efficient realistic 3D surface reconstruction.