Mago: A new approach for orthophotos production based on adaptive mesh reconstruction

Orthophotos are one of the most common and typical products of a photogrammetric post-processing and, since the diffusion of specific software, their generation and usage have become even more widespread. In spite of it, some issues remain on the accuracy of orthophoto reconstruction, which is often downgraded by the introduction of meshes and Digital Surface Models to be used as surfaces representing the object. The use of a more accurate and reliable input, such as a point cloud, makes these approximations avoidable. For this reason, a new approach, termed MAGO (Adaptive Mesh for Orthophoto Reconstruction), is here delineated and proposed. The input data of the procedure are the user-defined orthophoto plane, the image and its internal and external orientation parameters, and a point cloud representing the object. Each pixel of the image is projected on the orthophoto plane at its original resolution via an iterative process, which builds an adaptive mesh, defined by means of the three best fitting points, where the collinearity rays and the point cloud intersect. After an overview on the method and its innovative features, an example on a test case is reported, together with a comparison between MAGO's and another photogrammetric software results.