UNSUPERVISED STATISTICAL APPROACH FOR TREE-LEVEL SEPARATION OF FOLIAGE AND NON-LEAF COMPONENTS FROM POINT CLOUDS
Accurately classifying foliage and non-leaf components in point clouds is essential for remote sensing forest applications. Existing methods rely on radiometric attributes or local geometric features, often requiring time-consuming manual labelling. In this paper, we propose a statistical approach u...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2023-12-01
|
Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1787/2023/isprs-archives-XLVIII-1-W2-2023-1787-2023.pdf |