Affiliation:
1. Academy for Advanced Interdisciplinary Studies, Northeast Normal University, Changchun 130024, China
2. Shanghai Zhangjiang Institute of Mathematics, Shanghai 201203, China
3. Institute of Applied Physics and Computational Mathematics, Beijing 100094, China
Abstract
Three-dimensional reconstruction based on optical satellite images has always been a research hotspot in the field of photogrammetry. In particular, the 3D reconstruction of building areas has provided great help for urban planning, change detection and emergency response. The results of 3D reconstruction of satellite images are greatly affected by the input images, and this paper proposes an improvement method for 3D reconstruction of satellite images based on the generative adversarial network (GAN) image enhancement. In this method, the perceptual loss function is used to optimize the network, so that it can output high-definition satellite images for 3D reconstruction, so as to improve the completeness and accuracy of the reconstructed 3D model. We use the public benchmark dataset of satellite images to test the feasibility and effectiveness of the proposed method. The experiments show that compared with the satellite stereo pipeline (S2P) method and the bundle adjustment (BA) method, the proposed method can automatically reconstruct high-quality 3D point clouds.
Funder
Major Program of National Natural Science Foundation of China NSFC
National Key R&D Program of China
Key Projects of National Natural Science Foundation of China NSFC
Beijing Natural Science Foundation
Department of Science, Technology and Information of the Ministry of Education
Fundamental Research Funds for the Central Universities
Reference29 articles.
1. Zhang, K., Snavely, N., and Sun, J. (2019, January 27–28). Leveraging vision reconstruction pipelines for satellite imagery. Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, Seoul, Republic of Korea.
2. Qin, R., Song, S., Ling, X., and Elhashash, M. (2022, January 4). 3D reconstruction through fusion of cross-view images. Proceedings of the Recent Advances in Image Restoration with Applications to Real World Problems, London, UK.
3. Pursuing 3-D scene structures with optical satellite images from affine reconstruction to Euclidean reconstruction;Wang;IEEE Trans. Geosci. Remote,2022
4. Facciolo, G., De Franchis, C., and Meinhardt-Llopis, E. (2017, January 21–26). Automatic 3D reconstruction from multi-date satellite images. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Honolulu, HI, USA.
5. Epipolar arrangement of satellite imagery by projection trajectory simplification;Wang;Photogramm. Rec.,2010
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献