SUPERVISED CLASSIFICATION AND ITS REPEATABILITY FOR POINT CLOUDS FROM DENSE VHR TRI-STEREO SATELLITE IMAGE MATCHING USING MACHINE LEARNING
Image matching of aerial or satellite images and Airborne Laser Scanning (ALS) are the two main techniques for the acquisition of geospatial information (3D point clouds), used for mapping and 3D modelling of large surface areas. While ALS point cloud classification is a widely investigated topic, t...
Main Authors: | A.-M. Loghin, N. Pfeifer, J. Otepka-Schremmer |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2020-08-01
|
Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/525/2020/isprs-annals-V-2-2020-525-2020.pdf |
Similar Items
-
Potential of Pléiades and WorldView-3 Tri-Stereo DSMs to Represent Heights of Small Isolated Objects
by: Ana-Maria Loghin, et al.
Published: (2020-05-01) -
Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery
by: Stefan Bachhofner, et al.
Published: (2020-04-01) -
AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION
by: P. Kupidura, et al.
Published: (2016-06-01) -
An Edge-Sense Bidirectional Pyramid Network for Stereo Matching of VHR Remote Sensing Images
by: Rongshu Tao, et al.
Published: (2020-12-01) -
HYBRID-BASED DENSE STEREO MATCHING
by: T. Y. Chuang, et al.
Published: (2016-06-01)