  Recently, a new global Digital Elevation Model (DEM) with pixel spacing of
0.4 arcseconds and relative height accuracy finer than 2m for flat areas
(slopes < 20%) and better than 4m for rugged terrain (slopes > 20%) was created
through the TanDEM-X mission. One important step of the chain of global DEM
generation is to mosaic and fuse multiple raw DEM tiles to reach the target
height accuracy. Currently, Weighted Averaging (WA) is applied 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). However, evaluations show that WA is not the perfect DEM fusion method
for urban areas especially in confrontation with edges such as building
outlines. The main focus of this paper is to investigate more advanced
variational approaches such as TV-L1 and Huber models. Furthermore, we also
assess the performance of variational models for fusing raw DEMs produced from
data takes with different baseline configurations and height of ambiguities.
The results illustrate the high efficiency of variational models for TanDEM-X
raw DEM fusion in comparison to WA. Using variational models could improve the
DEM quality by up to 2m particularly in inner-city subsets.
