You've got a lot of very high pixel values in the red channel. I'm not sure where this noise originated (hot pixels or just a bad calibration), but you can remove most of those defects with a simple PixelMath expression. I wrote a quick example, where I check for each red pixel in the image and if it is greater than the average of the green and blue pixel by more than 0.1 then the red pixel is replaced by the green and blue average (giving kind of a neutral value).
Below is a screen shot of the PixelMath expression editor showing the math needed to do this fix. But, this should really be done before the image is converted to JPEG and perhaps even while the image is in linear format. However, you'll need to change the 0.1 offset to something lower when the file is still in a linear format.
With some further tweaks to the expression you could do a better job, like checking to see if the green and blue average is above a certain level (so that you don't affect any bright features that are actually okay).
Also, a copy of the corrected image (after the PixelMath fix). Note, after removing a large part of the red noise I notice that there are also a fair number of bright greenish pixels. Well, you could then process the image a second time to remove those defects (with probably a different offset factor, probably not the 0.1 I used for the red correction). Note, I just guessed at that offset value, although I did measure a few pixels and the mean of the background image to get some idea of the general brightness of the image.
You may also want to look at PixInsight's CosmeticCorrection tool, since that too can replace outlier pixels.
Edited by james7ca, 30 June 2019 - 12:44 PM.