Is the Old LinearFit Tool Better For Color Than SPCC
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- Опубликовано: 5 сен 2024
- If you are a PixInsight user, have you been trying to get color from mono data and feeling let down by spectrophotometric color calibration? There is a problem with SPCC. It frequently yields washed out colors like salmon-pink reds and drab, faded blues. So, how does it compare against the color gotten from the older LinearFit tool? We'll put SPCC and LinearFit to a side-by-side test using the same information and processing of vdB 132. When SPCC is weighed and measured against LinearFit, it is found wanting.
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Real advice here. I don’t know why they keep coming out with new color cal tools that just make images terrible.
True. One can play with the SPCC outcomes, of course, by changing the white references, modifying the QE curves and filters and so forth, but then one has to wait for each new rendition to see where that's going to go. The Linear Fit tool gives a good outcome almost every time, and then I can modify the color temperature and shift the HSL and remix the channels and see the outcomes live as I work, which I find gives faster, better outcomes.
Thanks for making this so interesting. You must've done this for a while. 😊
I fell in love with the stars when I was a kid but diverted in my university years into the field of psychology and emergent intelligence. But I never lost my love of the sky.
@@SKYST0RY My biggest mistake was trying to do too much when I was younger. I was all over the place trying new things. I decided last year to get serious with the hobby by starting slowly with an astrograph on a simple tripod and capturing images of the Sun and the Moon. Then late last year a colleague gave me a small donation towards a tracking mount which allowed me to complete the rig early this year. I was floored that I could image DSOs from my skies fairly easily. So I’m getting comfortable with the acquisition side and the new Ares camera has really shown promise I could never imagine. The next step is learning the basic image processing side. So much to learn for my 68 year old brain.
@@IronMan-2024 The sky, like life, is so interesting. It is tempting to try to do it all and spread to thing. I think I was in unversity five years before I finally decided on my fields of specialization. Too much that is too interesting.
Interesting.
This was precisely my thoughts when I saw one fellow on UTube using Auto Linear fit Script….the result was the background color was also better balanced….I like your idea of using SPCC for star color and also merging the best of linear fit and SPCC….the resultant green is easily dealt with…one person said to use the lowest mean so that noise would not be amplified…have you tried that…would that be also a good approach?
I experimented with the lowest median but not the differences based on mean. I found via experimentation that the highest median consistently gives the best results. Noise is easily removed these days.
How about in case of OSC cameras, should I separate the channels and apply same approach or the fact that it is an OSC camera makes it not applicable? Thx
You could separate the channels and try running them through Linear Fit and the compare that to results from SPCC. Bear in mind, SPCC isn't a bad tool, and often it gives okay results. But you'll get more intense color pretty typically if you use Linear Fit and select the image with the highest median as your reference. Alternatively, you could run SPCC repeatedly using other white references, but that is very time consuming. There is no "correct" color balance anyway. Every camera perceives color differently, and we humans also perceive it differently, partly due to differences in our eyes, and partly due to differences in neurological processing. Color is subjective. Find the color balance that works for you.
The problem when SPCC do not work good is 99% bad background reference
Often the case.