I have decided to compare non-calibrated lights with flat and bias calibrated ones, to pick the most optimal pre-processing routine for my data.
Variables:
10-minute Ha 3nm lights (33 of them)
151 bias frames
50 flats
CCD temperature: -15C
Camera: QSI 690
Noise indicators: AVG (Average Absolute Deviation) and MAD (Median Absolute Deviation)
All subs were star-registered against the same sub and also the same sub has been used as a reference for integration (Linear Fit with the same parameters).
Results:
Single entire subs:
Not calibrated: AVG = 27.1, MAD = 23.7
Calibrated with Master Bias and flats: AVG = 27.077, MAD = 24.054
Calibrated with SB and flats: AVG = 27.056, MAD = 24.028
Single subs - small area with background only:
Not calibrated: AVG = 24.4, MAD = 23.7
MB and flats: AVG = 24.644, MAD = 24.579
SB and flats: AVG = 24.667, MAD = 24.748
These results suggest that there is a bit of noise being injected into single subs while calibrating them with bias and flats, while at the same time there is little or no difference between calibrating with either Master Bias and Super Bias, at least in terms of noise.
Stacks of 33 subs:
Entire subs:
Not calibrated: AVG = 7.801, MAD = 4.685
MB and flats: AVG = 7.798, MAD = 4.609
SB and flats: AVG = 7.937, MAD = 4.703
Stacks - the same small area with background only:
Not calibrated: AVG = 4.187, MAD = 4.206
MB and flats: AVG = 4.287, MAD = 4.295
SB and flats: AVG = 4.340, MAD = 4.357
Surprise surprise. For this data set, the stack of subs calibrated with Master Bias apparently injected less noise (and/or more effectively removed fixed patterns) than the same set of data calibrated with a Super Bias!
Out of curiosity, I have also subtracted New Master Bias from Old Master Bias (from over a year ago), and then aggressively stretched the difference. Then I repeated the same for Super Bias frames. The difference between two Super Biases resulted in somehow funny patterns, that are not present in the difference between Master Bias frames.
Mind you, mean ADU values for both differences were less than 0.5.
I think that in the end I managed to produce a few meaningless numbers
Thank you for reading.
Suavi
EDIT: Just read Rick's post - wondering if this difference between old and new bias frames indicates a drift of bias over time, or is it a result of the "amp glow" fix that QSI did a few months ago.