Round two!

If you are looking to compare the results of space-based images with ground-based images, then you have a whole lot of variables to deal with. Ignoring the atmospheric issue for the moment, the question really is not about pixels per-se. You are going to have differences due to pixel size, as well as scope focal length, scope aperture, overall field of view, etc.

Given you will be working with solar images, I am going to assume for the moment that the data will be well into the realm of shot noise limited. A solar imaging system, even one that uses a doppler tuned etalon to limit bandpass to the sub-angstrom level, should still be capable of producing strong signal, more than enough to render camera noise effectively moot. The only real exception might be if you are trying to measure solar granule motion in real time or something like that, which would require very short exposures. So I don't think that camera noise, or even camera FPN, is really going to be your largest concern.

The question has to do with image scale and FoV, really. Barring the unlikely scenario that all of your imaging systems are truly identical, with the only variable being whether they are Earth-bound or in space, image scale and FoV are going to be your primary variables that affect the data.

Image scale is relative to the pixel size and focal length. The actual formula is:

ImageScale = (206.265*PixelSize)/FocalLength

Where PixelSize is in microns, and FocalLength is in millimeters. If you have a 5 micron pixel and a 1000mm (1-meter long) focal length, then you have an image scale of 1.031"/px, or about one arcsecond per pixel.

The higher the image scale (which is actually a smaller image scale number), the higher the resolution of the system unless you have exceptionally bad seeing. A long telescope with small pixels is going to resolve considerably more than a short telescope with large pixels. Even if the two scopes use the same sensor with the same pixel size, the longer telescope is going to spread details over more pixels, so they will be more accurately resolved. That will usually result in discrepancies once the disparate data is registered.

The FoV is going to be dependent on the sensor size as well as the focal length. If you had 5 micron pixels, with a 1024x1024 pixel sensor, your FoV would be ~17 arcminutes, or about one quarter of a degree, on either side. A 500mm (half meter long) telescope would give you an FoV of about half a degree, a 2000mm (two meter long) telescope would give you an FoV of about 1/8th of a degree. Professional telescopes tend to have longer focal lengths, however I honestly don't know what kind of space-based systems you might be using or what focal lengths they may have.

Now it is possible to register images with disparate image scales and fields of view. The registration algorithm will identify the stars in each image relative to a single reference, and adjust each frame accordingly. Advanced registration algorithms can also correct for distortion within the image, as well as perform simple translations and rotation. The thing about registration, however, is it will change the nature of the data. Depending on exactly what aspects you correct, you may end up with interpolation artifacts, and worse, they can be non-uniformly applied throughout the field.

Registration issues can be worse if you choose a poor reference frame. Some registration tools allow you to plate solve your images and generate a synthetic starfield from the plate details. You can then use the synthetic, distortion free and accurately modeled starfield as your registration reference, which can minimize compounding artifacts due to poor reference selection. However, it will not eliminate them.

If your individual images are indeed shot noise limited, then I honestly do not see the camera noise really being an issue. Every camera has FPN and DFPN. The former could limit SNR if your exposures are too bright, and the latter could limit SNR if your exposures are too dim. However proper calibration with flats and darks should correct most FPN, leaving you with just the temporally random noise. Even if you had 8-10e- worth of read noise and a couple e- worth of dark current, if your signal is even just 200e- or greater, you would completely swamp the camera noise, rendering it effectively meaningless.