Uncertainty-Guided Depth Fusion from Multi-View Satellite Images to Improve the Accuracy in Large-Scale DSM Generation

Uncertainty-Guided Depth Fusion from Multi-View Satellite Images to Improve the Accuracy in Large-Scale DSM Generation

The generation of digital surface models (DSMs) from multi-view high-resolution (VHR) satellite imagery has recently received a great attention due to the increasing availability of such space-based datasets. Existing production-level pipelines primarily adopt a multi-view stereo (MVS) paradigm, whi...

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Bibliographic Details
Main Authors: Rongjun Qin, Xiao Ling, Elisa Mariarosaria Farella, Fabio Remondino
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Remote Sensing
Subjects:
satellite photogrammetry
multi-view stereo
depth fusion
digital surface models
dense image matching
uncertainty
Online Access:https://www.mdpi.com/2072-4292/14/6/1309

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