The article is devoted to the development of an algorithm for three-dimensional terrain reconstruction based on single satellite images. The algorithm is based on the algorithmic formation of three-dimensional models based on the output data of two deep learning models to solve the problems of elevation restoration and instance segmentation, respectively. The paper also presents methods for processing large satellite images with deep learning models. The algorithm proposed in the framework of the work makes it possible to significantly reduce the requirements for input data in the problem of three-dimensional reconstruction.
Keywords: three-dimensional reconstruction, deep learning, computer vision, elevation restoration, segmentation, depth determination, contour approximation