  For future solar missions as well as ground-based telescopes, efficient ways
to return and process data have become increasingly important. Solar Orbiter,
e.g., which is the next ESA/NASA mission to explore the Sun and the
heliosphere, is a deep-space mission, which implies a limited telemetry rate
that makes efficient onboard data compression a necessity to achieve the
mission science goals. Missions like the Solar Dynamics Observatory (SDO) and
future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on
the other hand, face the challenge of making petabyte-sized solar data archives
accessible to the solar community. New image compression standards address
these challenges by implementing efficient and flexible compression algorithms
that can be tailored to user requirements. We analyse solar images from the
Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect
of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image
compression at different bit rates. To assess the quality of compressed images,
we use the mean structural similarity (MSSIM) index as well as the widely used
peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context
of solar EUV images. In addition, we perform tests to validate the scientific
use of the lossily compressed images by analysing examples of an on-disk and
off-limb coronal-loop oscillation time-series observed by AIA/SDO.
