Jupiter with Io in transit - 2 Oct 2022

[Magnum]

great job,

[geoflewis]

4 hours ago, geoflewis said:

This has been a great discussion about best capture and processing techniques, really apprciate all the contributions from everyone.

So based on @neil phillips findings, I decided to use PIPP to join 4 x 2 min SERs from the end of my capture sequence. I ran that through AS3! at 10% to create a reference frame, which I then used to de-rotate the 8 min PIPP SER in WinJupos. Took this back int AS3! and grabbed best 5%, into Registax6 for wavelets, then Affinity photo for final colour saturation and levels tweaks, plus a slight denoise for a smoother look and feel. Et voila....

Nice round moon shadow, with no smearing, so I think the jury is in. No need for lots of separate SERs, just go long with the capture in good seeing, or join separate shorter SERs in PIPP and WinJupos de-rotate will handle it....

Thanks everyone, it's been a huge learning experience for me. I now doubt that I'll ever go back to using the ASI290MM for multiple R,G,B captures with all the headache of processing and combining those 15+ videos and then having to fix a smeared transit in post processing.

So an update for anyone interested on how long can you go....?!! I joined all my SERs (so over 20 mins) from the session on 2 Oct in PIPP and tried to stack best 5% of those and it fell over.

It seems that there might be a cut off to the elapsed time after which PIPP and/or WinJupos doesn't know what to do with the transiting moon and shadow without smearing. Probably more testing is required, but actually the limb edges start to get messy if one goes too long, so I'm concluding that ~6 mins per SER is probably the sweet spot if there is a transit in play and maybe 8 mins to 10 mins, if there's no transit happening.

Of course YMMV.

[geoflewis]

I decided to put 2 images together, annoted for submition to Dr John Rogers, Dir Jupiter Section, BAA. The first shows Io's 1st contact as it commenced its transit, the 2nd as already posted and discussed here.

It's interesting to note that the detail in each is almost the same, despite the second image comprising nearly x7 the data. It just goes to show that very long capture sequences don't really add much in average seeing conditions - something about silk purses and cows ears comes to mind....

Edited October 5, 2022 by geoflewis