A Comparative Study on Deep-Learning Methods for Dense Image Matching of Multi-angle and Multi-date Remote Sensing Stereo Images. (arXiv:2210.14031v1 [cs.CV])

Deep learning (DL) stereo matching methods gained great attention in remote
sensing satellite datasets. However, most of these existing studies conclude
assessments based only on a few/single stereo images lacking a systematic
evaluation on how robust DL methods are on satellite stereo images with varying
radiometric and geometric configurations. This paper provides an evaluation of
four DL stereo matching methods through hundreds of multi-date multi-site
satellite stereo pairs with varying geometric configurations, against the
traditional well-practiced Census-SGM (Semi-global matching), to …

arxiv image images remote sensing study