In response to the problem of insufficient accuracy in processing dense matching point cloud data of drone images using traditional interpolation algorithms, this study proposes an improved irregular triangulation interpolation algorithm. By filtering the seed points of the triangulation network and adding auxiliary points with maximum boundary values, it is more suitable for dense matching point cloud data. By comparing with traditional Kriging interpolation algorithms, inverse distance weighted interpolation algorithms. The irregular triangulation interpolation algorithm is used to process DEM models generated from dense matching point cloud data, and it is concluded that the improved algorithm proposed in this paper can more accurately reflect terrain features.

Xufeng Gao, Wei Su. Research on Modeling Method of Digital Elevation Model for Dense Matching Point Cloud Images in Complex Environments. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 13: 76-81. https://doi.org/10.25236/AJCIS.2023.061312.

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