Quote:
Originally Posted by multiweb
Yes, my thoughts exactly. So to mitigate the variability of quality in 10 nights, let's say I have 10 sets/sessions of ~50x10min; if I grade, register and take 5 calibrated subs of each set and make 10 new batches of 50 subs my new batches will contain roughly the same range of "good and bad" frames. So when I create my masters from the batches they should be more or less similar SNR? Would that be a better, more uniform, approach to this?  |
I think a mix and match approach is a good idea.
Quote:
Originally Posted by multiweb
Also you said you'd do a straight combine of the masters, without data rejection this time. Any reason? Would you reject too much overall?
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So long as you're not doing small batches the rejection in each batch should be sufficient, especially since you're integrating a lot of data and the contribution from each sub is small. A second round of rejection is going to reduce SNR without any benefit.
Cheers,
Rick.