Regarding SNR calculations. I was using Starlink GAIA to help determine optimal aperture using SNR based on photon counts. GAIA reported counts and count_err so SNR was simply count/count_err and for similar sized apertures to those in automatically sized in AIJ I was getting ~90 to 100 SNR. The SNR calculation in AIJ appears to be calculated on flux /flux _err so same in principle (assuming counts is equivto flux) but in AIJ the SNR is consistently 0.003 ie error much greater than the measurement. So I'm not sure how to interpret AIJ SNR calc
I re-checked the FITS data files. The version I was using had gone through Pixinsight to align them (I didn't realise alignment wasn't strictly necessary with WCS) and for some reason the resultant files had much lower counts. I reverted back to the original files and all is good - decent counts and SNR.
I am now comparing the aperture sizing AIJ calculates versus doing a manual set of trial apertures in Starlink Gaia which tends to show a higher SNR for smaller apertures compared to AIJ
Sometimes smaller SNR can be obtained with smaller apertures but only at the expense of higher BIC values. If the BIC starts going up as apertures get smaller and SNR goes down, it is probably best to back off a bit.
I had similar unreasonable SNR values when I did photometry on 32 bit float format FITS files - so maybe this is the same in your case. The values when the files were 16 bit integer format were reasonable.
When I multiplied the F_* (net (background subtracted) integrated counts in the aperture in ADU) and the F_S (number of sky background counts per pixel in ADU) values in the Error formula on page 11 of this...
Even if floats have been normalized, the SNR calcc should be correct as long as you have similarly compensated noise parameters (read noise, dark current, gain) set correspondingly. Do you have an example image that you can provide that is not working? We'd also need corresponding read noise, dark current, and gain that and been adjusted appropriately if the float files have been normalized.
Do you have a googledrive or dropbox? If so, just upload there and let us know the link. We really just need 1 file. Note that we'll need the associated detector read noise, dark current, and gain. If the images have been calibrated, normalized, etc., the read noise, dark current, and gain should also be adjusted appropriately.
I have linked 16bit and 32bit files - both of these were processed using Siril 1.2.0-beta1. For both measurements gain is 1.0, dark current and read noise are 0.0. While these values are of course not realistic they should give some idea that the calculation is working. My thinking is that the formula used is valid for values > 1 which should work when we are thinking of signal counts. For values < 1 the square root of the noise value will rise faster than that of the signal so it can't be right can it?
It looks like the 32 bit image has been normalized. When the calibration/image processing software changes the overall scaling of the image, it is effectively changing the gain. For instance, if your initial image values ranged from 0 to 65K, and the calibrated image ranges from 0 to 1, then the gain has changed by a factor of 64K! So, you'll need either have your image processing software NOT normalize the image values, or you'll need to know the normalization factor and include that factor in the gain setting in AIJ (multiplied by the actual detector gain). That will scale the pixels values back up for purposes of calculating SNR.