I assume each group of images will have it's own calibration data. If you just put all the data into WBPP, but with a manually selected registration image (ideally an image with lots of stars) that will define the frame for the combined image, then WBPP will calibrate each group separately, then align them all to your selected reference, and then integrate them all. WBPP has other options, but that should be the default action.I have to register all different stacked images and than integrate them?
Second thougt of mine was to stitch all picks in the stetched state - so to say - when they are allready finallly processed.I assume each group of images will have it's own calibration data. If you just put all the data into WBPP, but with a manually selected registration image (ideally an image with lots of stars) that will define the frame for the combined image, then WBPP will calibrate each group separately, then align them all to your selected reference, and then integrate them all. WBPP has other options, but that should be the default action.
I mean dark frames and flat frames (i.e. each different instrument / camera combination will have separate calibration data). While it is possible to integrate each group separately, then combine the groups, WBPP will probably do better if you combine them all in a single integration (since it will then manage normalisation and scaling on a frame-by-frame basis).What do you mea by "it's own calibration data"?
With that many data sets I would run each one separately and combine at them afterwardsGot you! Whish, it wouldn't be that complicated. We are talking about 7 or 8 different data sets.
But anyway, thank you so much for your most kind support and advice.
I am more than thankfull...
Take care and - again - thank you,
Christian
Out of interest, why? (I would only run them separately if I had problems running them in a single batch, mainly because a single run allows ImageIntegration to scale and normalise on a frame-by-frame basis across the entire set).I would run each one separately and combine at them afterwards
Largely because 7 or 8 datasets will have widely varying quality (halos, noise, FWHM etc) and importantly orientation. I would rather have 7 different masters to assess and combine than 100‘s of frames. Whenever I have processed a collaborative effort cropping the combination has been tricky, unless every contributor captures at the same rotation angle. I would also be tempted to do DBE, SPCC and maybe even some judicious NR before combining. Sometimes leaving a sub par set out of the combination leads to an improvement.Out of interest, why? (I would only run them separately if I had problems running them in a single batch, mainly because a single run allows ImageIntegration to scale and normalise on a frame-by-frame basis across the entire set).