You have to be more careful about what you mean by "these practices".

False-color images, in which some quantity you care about (e.g., water vapor, [1]) is projected into a map or spatial coordinate, are pervasive throughout the sciences. Nobody would seriously contemplate putting some kind of interpretive warning on such images, because we all know you can't see water vapor or ocean salinity directly.

From such non-deceptive cases, you have a slippery slope.

After you work with spatially-mapped imagery for a while, it's natural to insert (invisible) infrared channels of an earth-observing satellite as the red channel of an RGB image. Similarly, it's natural to color-code certain spectral bands of solar images, in extreme UV, as a shortcut to highlight flares, even though you can't come close to seeing these bands directly [3] [4].

It's also natural to adjust the contrast or related properties like white balance, of planetary images. After all, your own monitor is adjusting the contrast through a gamma correction [2] that isn't well-standardized.

I think people have complained about these kinds of enhancements before -- in some cases, with reason -- so now you do in fact see disclaimers about contrast enhancement on NASA images. [5] If you pay closer attention, I think you will notice these disclaimers, too. (I did not cherry-pick [5], I just looked at the JPL news feed until I came to a news release that might involve a real-world scene - the next example I saw was [6], which also has a disclaimer).

I haven't been involved in that many NASA press releases, although I have done work with the investigator mentioned in [1]. Of course, for a press release, you have to simplify complex issues and make analogies and all that stuff. Hopefully the science comes through, and also hopefully, there is a link to the published paper which has the technical details. That last is the key, because it offers some guarantee that the result was vetted, and a method to review the original data.

The amount of care that goes in to getting calibrated data is hard to convey. It's critically important, and all the science done at NASA and with NASA data depends on it.

For instance, just think for a bit about all the geometric and photometric calibration that had to be done to mosaic up the little self-portrait image of Curiosity. They had to back out the joint angles of all the actuators from the camera all the way back to the robot, and color-correct for different exposures, and rescale to account for distance differences, and account for parallax with a camera lens model (which itself had to be calibrated) and .... And that's just for a non-science image. It doesn't really need to be photometrically calibrated.

The actual science images would have much more careful localization and photometric calibration. A person I work with routinely cross-calibrates in-situ instrument footprints of size ~1mm onto this imagery to get the correspondence between mineral grains (visible in camera images) and mineralogy information.

For instance, the widely-used CAHVOR(E) geometric camera model that maps pixel indexes (i,j) in the CCD array, to physical locations in space, was invented in 1978 at JPL [7]. And things have come a long way since then. As a sample of the documentation of the MAHLI camera that took those images, see [8]. That paper was followed with an even more detailed post-landing calibration document [9] - about 100 pages, condensed from years of R&D and calibration.

What is my point? First, it is always a stretch to map the data from a special sensor like that back to an RGB image. And second, if you really do want to understand the relation of what you're seeing back to the original physical setup (i.e., learn the "truth" as revealed by the measurement), you have to do a lot of geometric/photometric analysis. And third, rather astonishingly, that analysis is also done routinely, and published for whoever wants to read/critique/improve.

[1] https://www.jpl.nasa.gov/spaceimages/details.php?id=pia21209

[2] https://en.wikipedia.org/wiki/Gamma_correction#Windows,_Mac,...

[3] https://www.nasa.gov/content/goddard/how-sdo-sees-the-sun

[4] https://www.nasa.gov/content/goddard/sdo-aia-171-angstrom/

[5] https://www.jpl.nasa.gov/news/news.php?feature=7137

[6] https://www.jpl.nasa.gov/news/news.php?feature=7118

[7] https://www.sciencedirect.com/science/article/pii/0146664X78...

[8] https://link.springer.com/article/10.1007/s11214-012-9910-4

[9] https://www.researchgate.net/publication/278728737_Curiosity...