Comparative analysis of monocular depth estimation in satellite two-dimensional images - Kozachuk, O.O. (Problems of Informatization and Management, 2025)
With the rapid growth in the use of satellite mapping services, there is a need for simple and effective methods and means of constructing 3D (three-dimensional) reconstructions of terrain using only 2D (two-dimensional) images as input, which ensure the reproducibility and comparability of results in applied urban analysis and navigation tasks. Monocular depth prediction models are a tool for formalizing such processes, as they allow the relative structure of a scene to be reconstructed with a minimum amount of input data, which helps to assess the relief and height contrasts of objects. Despite the availability of services that allow obtaining three-dimensional satellite images, their limitation is that they are either commercial or do not work in Ukraine. That is why the task is set to build such a model that will solve these problems. The paper considers pre-trained models and their application to satellite images. The models considered were trained on different datasets, so the quality of reconstruction was evaluated on pre-trained models, selected by quality, and trained on a dataset of satellite images. The results of the study can be used to develop methods for aircraft navigation, reconstruction, and terrain analysis, and allow for simpler and faster 3D reconstruction of arbitrary objects, although they are inferior in accuracy to resource-intensive methods. It should be noted that the proposed methodology allows the results to be applied to applied problems in other domains. It is reproducible, easy to use, and suitable for further scaling to larger samples and metric calibration problems.