The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume XLII-2/W16
https://doi.org/10.5194/isprs-archives-XLII-2-W16-243-2019
https://doi.org/10.5194/isprs-archives-XLII-2-W16-243-2019
17 Sep 2019
 | 17 Sep 2019

AUTOMATED CHAIN FOR LARGE-SCALE 3D RECONSTRUCTION OF URBAN SCENES FROM SATELLITE IMAGES

S. Tripodi, L. Duan, F. Trastour, V. Poujad, L. Laurore, and Y. Tarabalka

Keywords: 3D Reconstruction, Satellite Images, Stereo Pair, Deep Learning, U-Net

Abstract. Automatic city modeling from satellite imagery is a popular yet challenging topic in remote sensing, driven by numerous applications such as telecommunications, defence and urban mamagement. In this paper, we present an automated chain for large-scale 3D reconstruction of urban scenes with a Level of Detail 1 from satellite images. The proposed framework relies on two key ingredient. First, from a stereo pair of images, we estimate a digital terrain model and a digital height model, by using a novel set of feature descriptors based on multiscale morphological analysis. Second, inspired by recent works in machine learning, we extract in an automatic way contour polygons of buildings, by adopting a fully convolutional network U-Net followed by a polygonization of the predicted mask of buildings. We demonstrate the potential of our chain by reconstructing in an automated way different areas of the world.