Hi Rodolphe,
Many thanks for uploading that.
I'm not seeing anything particularly worrisome, and AutoDev is - as explained - working as expected.
I'm not entirely sure what the screenshots are intending to show though? They both appear to be a preliminary/diagnostics AutoDev, as the dataset appears to be vastly oversampled and stacking artefacts are still visible.
All optical trains come with a distinct diffraction pattern; the very act of imaging through a circular opening will cause point lights to spread (diffract) light into neighbouring pixels. At the very least, your optical train will show an
Airy disc profile. This is natural, and will - if stretched correctly - show up spots of light tapering off into neighbouring pixels. If stretched
incorrectly, however these will appears as overexposed, whited out circles.
Stars are then further "smeared out" (convolved) by atmospheric conditions (aka 'seeing') according to a roughly Gaussian pattern.
The final resulting stellar profile of a non-overexposing star, is therefore a central point of light that tapers off. Please note that they are not "halos" in the sense of the
optical phenomenon.
The final resulting stellar profile of a non-overexposing star, is
also virtually identical to the Point Spread Function in your image; the full convolution kernel by which the point light was "blurred" (convolved).
The proper way to deal with the above mechanisms by which stellar profiles come about, does
not have anything to do with stretching. In fact, stretching has no bearing on the presence of these stellar profiles vs other detail). The proper way to address the above mechanisms, is to apply deconvolution (e.g. convolution, but in reverse). Selective editing (in various degrees of acceptability) should be considered a last resort.
Preparing your data for deconvolution is actually the focus of half the workflow in StarTools. So for your specific dataset this means;
- AutoDev to see what we got.
- Bin to convert oversampling into noise reduction (sorely needed for deconvolution!)
- Crop away stacking artifacts.
- Wipe
- Final AutoDev with RoI over a sample of the detail your are interested in.
That gives you something like this;
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- StarTools_2808.jpg (289.88 KiB) Viewed 5748 times
Though noisy and suffering from some coma, deconvolution still works reasonably well on your dataset;
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- Selection_732.jpg (58.82 KiB) Viewed 5748 times
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- Selection_731.jpg (76.15 KiB) Viewed 5748 times
Note how decon works two ways here to alter the dynamic range locally at a very fine (finest) level;
- It reduces the area the stellar profile occupies (ST's implementation even does this for overexposing stars to a degree)
- it increases the definition of the restored point light versus its surroundings
both help define stars better; they directly increase the dynamic range and therefore contrast of star vs stellar profile.
Deconvolution is not a silver bullet of course. As said, from there you can use the Shrink module to taste, and particularly its Unglow feature (I used the same mask Decon made);
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- Selection_734.jpg (246.95 KiB) Viewed 5748 times
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- Selection_733.jpg (245.27 KiB) Viewed 5748 times
Beyond that, you can hold out for better atmospheric conditions, particularly transparency; e.g. being free of cloud/dust/haze that can otherwise cause light to scatter, causing true halos.
Hope this helps!