2022-05-29: APP 2.0.0-beta2 has been released !
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Why does my H-a Look so Bad?
Whenever I run an Analytical Graph and sort on Quality, H-a always looks relatively poor compared to the other filters. See attached screen shot for an example. On the night the H-a data was collected, the moon was around 1st quarter and low in the southwest. About 70 degrees away from the target M33.
I suppose what I am really asking is how do I interpret the various statistics APP computes for each sub?
At this moment just sorting on Quality, my first impulse is to delete the entire batch of H-a.
Looking at the stats, it seems that the H-alpha subs have less data, maybe due to not enough exposure (which would make sense). There are less stars detected in each sub and the overall registration of those is slightly less nice then those in the other data (still very good though). All of these factors count for a different quality score which takes stats like this in consideration (star shape as well).
@vincent-mod That would make sense since it is a comparison of broadband to 3nm H-a. (Incidentally, after finishing that target I lengthened all of my narrowband exposures to 300 seconds.)
What is Dispersion and Background?
Background is the background level of the sky basically and dispersion is the variation around this, Mabula once explained it as follow:
Dispersion: each image has a peak in their histogram, usually this peak corresponds more or less to the sky background in the image. This peak can be regarded as the central value of the pixel distribution of the image and the average/mean values are calculated central values which will be more or less the same as the location of the peak/sky background. Now the way the data is spread around this central value is called dispersion. If the peak is very sharp, you have small dispersion, if the peak is wide, you have a high dispersion value. Dispersion is also called scale, and can be calculated in many ways ! the standard deviation (root of variance) is a way, as is MAD, Median Absolute Deviation.
Thank you, that is helpful indeed.
Looking to the example I posted, the H-a should have much less dispersion, darker background, and higher SNR vs. the broadband data. I guess I should not even be comparing the two directly though the analysis graph tempts this.
If I could revisit this topic with you Vincent:
This morning I thought it would be a good idea to do a "status check" on the narrow band (S, H, and O) lights I have collected thus far on NGC 6888. I don't have enough to integrate, these were "pre-processed" through Normalization to generate analytical graphs. My practice has been to delete subs below the 70th percentile.
In the past I processed everything together (narrow and broad band data, all sessions) and would get quality scores from 400 to 800. H-a generally having the lower numbers in that range.
This mornings numbers were crazy good: 94 subs and Quality scores ranged from 1700 to 2400!
As nice as those numbers are, I don't think there has been any sudden change to my equipment or techniques that would make a 300% improvement. Maybe it was just wrong to normalize broad and narrow bands together?
So my question is to get a true measure of quality for each filter, should I process each filter separately?
Sure, happy to help.
The quality scores are not really handy to compare different data indeed. They are relative to the other data, which is why you get higher scores when you exclude the others. In between it does give a good idea, so if you really use the score to judge for quality, I would do it per filter.