A review of 3D reconstruction from high-resolution urban satellite images. Issue 2 (17th January 2023)

• Record Type: Journal Article
• Authors: Zhao, Li; Wang, Haiyan; Zhu, Yi; Song, Mei
• Is Part Of: International journal of remote sensing. Volume 44:Issue 2(2023)
• Page Start: 713
• Page End: 748
• Publication Date: 2023-01-17
• Subjects: Urban satellite image -- 3D reconstruction -- dense matching -- multi-view DSM fusion; Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2023.2169844
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Automated 3D reconstruction based on satellite images has become a research hotspot at the interdisciplinary of photogrammetry and computer vision. The 3D results based on satellite images will play a key role in the understanding of global 3D information, monitoring of national geographic and urban construction, with the inherent advantage of satellite images in global coverage. Researchers have devoted substantial effort to develop state-of-the-art 3D reconstruction methods for two-view satellite images and multi-view satellite images. However, it is still a challenging task to obtain complete and accurate 3D results with satellite images due to the difference in shooting angles between satellite images, exposure differences and building occlusions in urban scenes. In this paper, we execute theoretical analyses and experimental evaluations about the popular 3D reconstruction methods towards satellite images following the order of two views to multiple views: (1) The advanced dense matching methods aimed at satellite images are reviewed theoretically and evaluated experimentally. (2) The state-of-the-art 3D reconstruction based on two-view satellite images are analysed in detail and experimentally evaluated with two-view WorldView-3 satellite images. (3) The popular fusion methods of multi-view DSM are analysed theoretically and assessed on multi-view WorldView-3 satellite images. This review will be helpful for researchers dedicated to enhancing the accuracy and completeness of the results of 3D reconstruction from urban satellite images.