Processing

I gathered around 50 hours of data, and used PixInsight’s SubframeSelector tool to whittle this down to the best 28 hours. The pre-processing took my PC almost 24 hours to complete.

Then it was onto the processing. The image was very noisy and ideally I’d have gathered much more data (I’ll explain why I didn’t in a moment), so to help once I’d stretched to non-linear I split the channels into RGB and ran NoiseXTerminator on each of the three.

I could see the red Flying Bat easily enough, but the blue Squid was very difficult to make out. This isn’t surprising as it’s mostly faint OIII. Fun fact: the Squid was only discovered in 2011! My solution was to import those RGB channels into Adobe Lightroom and study them carefully. The Squid wasn’t visible at all in the Red channel (not surprising as that maps to Hα). I could just about make it out in the Green channel, and again but even fainter in Blue. I made a few tweaks to those Green and Blue channels to bring the Squid out more, and then recombined the channels in PixInsight before continuing processing. This resulted in the Squid being much easier to see.

The final photo won’t win any awards, but I think it’s interesting because of the conditions under which it was taken: from a city centre using a small refractor and OSC camera. Tackling this target in particular made me want dark skies and a Mono camera, as really they’re needed to do it justice. But I still very much appreciate how simple data acquisition is with OSC. For more on this, check out my article OSC vs Mono from a City.

And as for why I didn’t keep collecting data? I’ve bought a new telescope, so started cannibalising astroimaging components from my Askar FRA400 to move over to the new rig. Stay tuned to Urban Astrophotography for more about this!