Fast and Accurate Satellite Multi-view Stereo Using Edge-Aware Interpolation

Wang, Ke; Frahm, Jan‐Michael

doi:10.1109/3dv.2017.00049

Cited by 4 publications

(2 citation statements)

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“…Beside vanilla SGM, the latter also implements the More Global Matching [14], using a modified cost aggregation scheme that aims for globally more consistent disparities. In order to avoid costly energy minimisation altogether, [65] construct dense correspondence maps from a sparse set of tie points, via edge aware interpolation.…”

Section: Related Workmentioning

confidence: 99%

“…To obtain a consistent representation of the surface, individual stereo models have to eventually be fused . This is typically realized during DSM generation, by binning 3D points from multiple models into a planimetric 2D grid, followed by various filtering strategies to derive a single elevation value per grid cell -accomplished often by simple median filtering [35,7,65]. [15] account for changing surface modes (e.g, vegetation) caused by different acquisition dates.…”

Section: Related Workmentioning

confidence: 99%

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Photometric Multi-View Mesh Refinement for High-Resolution Satellite Images

Rothermel¹,

Gong²,

Fritsch³

et al. 2020

Preprint

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Modern high-resolution satellite sensors collect optical imagery with ground sampling distances (GSDs) of 30-50cm, which has sparked a renewed interest in photogrammetric 3D surface reconstruction from satellite data. State-of-the-art reconstruction methods typically generate 2.5D elevation data. Here, we present an approach to recover full 3D surface meshes from multi-view satellite imagery. The proposed method takes as input a coarse initial mesh and refines it by iteratively updating all vertex positions to maximise the photo-consistency between images. Photo-consistency is measured in image space, by transferring texture from one image to another via the surface. We derive the equations to propagate changes in texture similarity through the rational function model (RFM), often also referred to as rational polynomial coefficient (RPC) model. Furthermore, we devise a hierarchical scheme to optimise the surface with gradient descent. In experiments with two different datasets, we show that the refinement improves the initial digital elevation models (DEMs) generated with conventional dense image matching. Moreover, we demonstrate that our method is able to reconstruct true 3D geometry, such as facade structures, if off-nadir views are available.

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Section: Related Workmentioning

confidence: 99%