Earth and Space: From Infrared to Terahertz (ESIT 2022) 2023
DOI: 10.1117/12.2664615
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Reliability-weighted fusion of multiview photogrammetric point clouds for 3D terrain reconstruction of the lunar surface

Abstract: Benefitting from advances in photogrammetry and computer vision, 3D point clouds generated from dense image matching have been proved to be an accurate, reliable, and cost-effective data source for lunar topographic mapping. To achieve a full coverage mapping of the lunar surface, a merging of point clouds generated from multiple observations is mandatory. Due to the limit of dense matching accuracy and accumulative registration errors, integrated point clouds normally suffer from disturbed stratification, ou… Show more

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“…The second step is the detection of outliers of DTM. Although the constraints based on elevation deviation have been applied in the filtering of individual point clouds (Balta et al, 2018) and the global registration of multiple point clouds (Xu et al, 2023), there are still fewer coarse outliers in the fused DTM, which are mainly distributed near the hole area (dome, impact crater, etc.). Thus, before filling the missing area in the fused DTM, a post-processing step should be conducted to detect and reject outliers, facilitating the subsequent hole-filling process.…”
Section: Outlier Detectionmentioning
confidence: 99%
“…The second step is the detection of outliers of DTM. Although the constraints based on elevation deviation have been applied in the filtering of individual point clouds (Balta et al, 2018) and the global registration of multiple point clouds (Xu et al, 2023), there are still fewer coarse outliers in the fused DTM, which are mainly distributed near the hole area (dome, impact crater, etc.). Thus, before filling the missing area in the fused DTM, a post-processing step should be conducted to detect and reject outliers, facilitating the subsequent hole-filling process.…”
Section: Outlier Detectionmentioning
confidence: 99%