Processing of old images (Learning info)

[Carole]

As the more experienced imagers will know, it is often a good idea to go back to old images and see if you can improve them with newly acquired post-processing skills.  For those new to, or considering imaging, the post-processing is probably more than 50% of the imaging skill and can take many years to learn.  Ten years on and I am still learning new techniques to bring out the best in images.

One of the things that I learned over the years was that during processing the stretching of the detail in the Nebulosity will often stretch the colour out of the stars, and will also stretch the stars as well.  Back in 2013 while visiting Olly Penrice in France he said to me that if you reduce the star size it will show off the Nebulosity better and over the years I have struggled to find a good method of doing this. 

I don't use Pixinsight, it is too mathematical for my liking, preferring to use Photoshop so I can see and control what I am doing. 

Olly also showed me a method of "bringing out the faint stuff" (Though this was more recently on a different forum). 

Earlier this week one of my non OAS Astro friends introduced me to Images Plus, which is now a free post processing software and I have been very impressed by the star reduction it can do.  You do have to be careful it doesn't muck up the nebulosity at the same time, but basically wanted to share this for those learning about images and those considering it.

I know there are some who prefer their images not to be processed this much, it is all a question of personal preference but certainly those on Astrobin of about 10,000 worldwide members seem to prefer to use star reduction (though some I think go too far with this).

This is my original image done in 2018



This is the image I have produced using Olly's (Bringing out the faint stuff technique and Images Plus star reduction. 



Images plus was a chargeable software but the author has now made it free to all.
I am happy to share this information if any-one wants a "lesson". 

Carole