@inproceedings{381ae8dba0cd449a93b619c7c2459006,
title = "Urban TanDEM-X raw DEM fusion based on TV-L1 and huber models",
abstract = "Recently, the TanDEM-X DEM has been produced as a global DEM with unprecedented relative accuracy. One important step of the chain of global DEM generation is to mosaic multiple raw DEM tiles by DEM fusion methods to reach the best possible target accuracy. Currently, Weighted Averaging (WA) is used as a fast and simple method for TanDEM-X raw DEM fusion in which the weights are computed from height error maps delivered from the Interferometric TanDEM-X Processor (ITP). In this paper, we investigate the efficiency of variational models such as TV-L1 and Huber model for the TanDEM-X raw DEM fusion task in comparison to WA. The results illustrate that using variational models can improve the quality of DEM fusion outputs especially for areas with high-frequency contents and more complex morphological features like urban areas. Using variational models could improve the DEM quality by up to about 1m.",
keywords = "Data fusion, Huber model, L1 norm total variation, TanDEM-X DEM, Weight map",
author = "H. Bagheri and M. Schmitt and Zhu, \{X. X.\}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "31",
doi = "10.1109/IGARSS.2018.8518870",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7251--7254",
booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",
}