Thank you. I learned some very useful things in this video. For example, I have the SETI Astro scripts loaded into PixInsight, but I had no idea that Find Background did what you demonstrated. I’ve always been a little bit anxious about picking the background sample, fearing I wasn’t doing it right. Now, thanks to Franklin, I can have it done automatically. And the main point of the video reinforces doing Linear Fit at the beginning of the process. This was 20 minutes well spent!
@randyshivak8785Күн бұрын
It was very interesting but clear as mud with your terms as early and late. 😢. Can you just tell me if you run the one on the left or the one on the right. The one on the left looks much better but for the life of me I not sure with your explanation.
@Hidden.Light.PhotographyКүн бұрын
I apologize about that :( I use the one on the left “SPCCLATE”. The main idea is to use SPCC as a final correction. Using SPCC as a final correction will retain the changes SPCC makes. I’m more than happy to reword differently and if you would rather email me with something you’d like explained differently you’re more than welcome to do that as well :)
@randyshivak8785Күн бұрын
@@Hidden.Light.Photography Thanks for the update. I’m very new to pixinsight so thank you for your expertise.
@Laurent_BARTHELEMY2 күн бұрын
the big difference , is the order you use ADBE , before or after SPCC...You change 2 factors , linear fit AND the order you use background extraction ..'.
@Hidden.Light.Photography2 күн бұрын
Exactly. Both of those will change what SPCC does. The reason they were ordered this way in the video was to answer the question of why not use SPCC to get rid of the color cast in the beginning. Doing so will still need the background extracted, thus rendering SPCC void.
@paulcopley27942 күн бұрын
To make a fair comparison of whether you need to do linear fit to get rid of the colour cast as well as SPCC, you should have done auto DBE before SPCCearly, not after - as stated you have changed two variables so the question of whether linear fit is needed has not been addressed.