Photometric multi-view mesh refinement for high-resolution satellite images

Rothermel, Mathias; Gong, K.; Fritsch, Dieter; Schindler, Konrad; Haala, Norbert

doi:10.1016/j.isprsjprs.2020.05.001

Cited by 17 publications

(6 citation statements)

References 32 publications

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“…This improvement of the positioning accuracy of satellite-based data, especially through new methods for RPCs bias correction, has been the point of convergence of several studies (Luong and Wolniewicz, 2005;Fraser et al, 2006;Xiong and Zhang, 2009;Tang et al, 2016;Dong et al, 2020;Marí et al, 2021;Junpeng et al, 2022;Loghin et al, 2022). Furthermore, various research contributions have been proposed for improving the automatic creation of 3D surface and building models, contributing at different stages of the reconstruction pipeline (Deilami and Hashim, 2011;Poli et al, 2015;Shean et al, 2016;Qin, 2016;Facciolo et al, 2017;Partovi et al, 2019;Perko et al, 2019;Qui, 2019;Rothermel et al, 2020;Breaban et al, 2022;.…”

Section: Related Workmentioning

confidence: 97%

Geometric Processing of Very High-Resolution Satellite Imagery: Quality Assessment for 3d Mapping Needs

Farella,

Remondino,

Cahalane

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In recent decades, the geospatial domain has benefitted from technological advances in sensors, methodologies, and processing tools to expand capabilities in mapping applications. Airborne techniques (LiDAR and aerial photogrammetry) generally provide most of the data used for this purpose. However, despite the relevant accuracy of these technologies and the high spatial resolution of airborne data, updates are not sufficiently regular due to significant flight costs and logistics. New possibilities to fill this information gap have emerged with the advent of Very High Resolution (VHR) optical satellite images in the early 2000s. In addition to the high temporal resolution of the cost-effective datasets and their sub-meter geometric resolutions, the synoptic coverage is an unprecedented opportunity for mapping remote areas, multi-temporal analyses, updating datasets and disaster management. For all these reasons, VHR satellite imagery is clearly a relevant study for National Mapping and Cadastral Agencies (NMCAs). This work, supported by EuroSDR, summarises a series of experimental analyses carried out over diverse landscapes to explore the potential of VHR imagery for large-scale mapping.

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Section: Related Workmentioning

confidence: 97%

Geometric Processing of Very High-Resolution Satellite Imagery: Quality Assessment for 3d Mapping Needs

Farella,

Remondino,

Cahalane

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Among the image sources, satellite images are one of the most used for DT creation, and the majority of the studies use 3D reconstruction based on stereo images [93]. This approach can provide abundant geoinformation with broad coverage.…”

Section: Image-based Dtmentioning

confidence: 99%

Toward 3D Property Valuation—A Review of Urban 3D Modelling Methods for Digital Twin Creation

Ying

Koeva

Kuffer

et al. 2022

IJGI

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Increasing urbanisation has inevitably led to the continuous construction of buildings. Urban expansion and densification processes reshape cities and, in particular, the third dimension (3D), thus calling for a technical shift from 2D to 3D for property valuation. However, most property valuation studies employ 2D geoinformation in hedonic price models, while the benefits of 3D modelling potentially brought for property valuation and the general context of digital twin (DT) creation are not sufficiently explored. Therefore, this review aims to identify appropriate urban 3D modelling method(s) for city DT, which can be used for 3D property valuation (3DPV) in the future (both short-term and long-term). We focused on 3D modelling studies investigating buildings and urban elements directly linked with residential properties. In total, 180 peer-reviewed journal papers were selected between 2016 and 2020 with a narrative review approach. Analytical criteria for 3D modelling methods were explicitly defined and covered four aspects: metadata, technical characteristics, users’ requirements, and ethical considerations. From this, we derived short-term and long-term prospects for 3DPV. The results provide references for integrating 3D modelling and DT in property valuation and call for interdisciplinary collaboration including researchers and stakeholders in the real estate sector, such as real estate companies, house buyers and local governments.

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“…It can generate textured building models. Rothermel et al [22] utilize multi-view high-resolution satellite images to realize mesh refinement. Many researchers have introduced deep learning theory into this technical framework in recent years and achieved good results.…”

Section: Related Workmentioning

confidence: 99%

A 3D Reconstruction Framework of Buildings Using Single Off-Nadir Satellite Image

et al. 2021

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A novel framework for 3D reconstruction of buildings based on a single off-nadir satellite image is proposed in this paper. Compared with the traditional methods of reconstruction using multiple images in remote sensing, recovering 3D information that utilizes the single image can reduce the demands of reconstruction tasks from the perspective of input data. It solves the problem that multiple images suitable for traditional reconstruction methods cannot be acquired in some regions, where remote sensing resources are scarce. However, it is difficult to reconstruct a 3D model containing a complete shape and accurate scale from a single image. The geometric constraints are not sufficient as the view-angle, size of buildings, and spatial resolution of images are different among remote sensing images. To solve this problem, the reconstruction framework proposed consists of two convolutional neural networks: Scale-Occupancy-Network (Scale-ONet) and model scale optimization network (Optim-Net). Through reconstruction using the single off-nadir satellite image, Scale-Onet can generate water-tight mesh models with the exact shape and rough scale of buildings. Meanwhile, the Optim-Net can reduce the error of scale for these mesh models. Finally, the complete reconstructed scene is recovered by Model-Image matching. Profiting from well-designed networks, our framework has good robustness for different input images, with different view-angle, size of buildings, and spatial resolution. Experimental results show that an ideal reconstruction accuracy can be obtained both on the model shape and scale of buildings.

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Photometric multi-view mesh refinement for high-resolution satellite images

Cited by 17 publications

References 32 publications

Geometric Processing of Very High-Resolution Satellite Imagery: Quality Assessment for 3d Mapping Needs

Geometric Processing of Very High-Resolution Satellite Imagery: Quality Assessment for 3d Mapping Needs

Toward 3D Property Valuation—A Review of Urban 3D Modelling Methods for Digital Twin Creation

A 3D Reconstruction Framework of Buildings Using Single Off-Nadir Satellite Image

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