![](bg7.png)
lowed by the reconstruction process. While simple
measures (like PSNR or SSIM) are sufficient here, it
is much more challenging to measure the similarity
between images that have been captured using differ-
ent sensors, at various spatial resolution. An example
of such images was shown earlier in Fig. 1b—I
(h)
and
I
(l)
i
were captured by different satellites, and certainly
the reconstructed image would be visually different
from I
(h)
. Importantly, the differences related to the
detail level may be negligible compared with those
incurred by the global variations. We have found the
keypoint detectors to be quite promising here (Kawu-
lok et al., 2017) and we will consider employing them
to evaluate the fitness. Overall, we currently explore
how to exploit the proposed framework to adapt an IM
alongside an SRR technique to images acquired by a
given sensor, which will be an important step towards
deploying SRR in real-life scenarios.
ACKNOWLEDGEMENTS
The reported work is a part of the SISPARE project
run by Future Processing and funded by European
Space Agency. In addition, the authors were partially
supported by Institute of Informatics funds no. BK-
230/RAu2/2017 (MK) and BKM-509/RAu2/2017
(DK).
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