Quote:
Originally Posted by rogerg
Jace,
If I understand you correctly, then providing the background levels are normalised between the exposures as you say (eg to 50), there is no need to know the exact relationship between the filters? ... because whatever the relationship is, they're all now equal.
Thanks,
Roger.
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No, normalising (aka equalising) the individual RGB component images does not alter the relationship between the filters i.e. it is not trying to compensate for filter transmission characteristics or CCD spectral response.
What normalising the background level does is provide consistency across all component RGB images allowing the colour weight ratios to be true (as validated via G2V calibration).
If you don't normalised the individual RGB component images before colour combining, you need to alter your colour weights to compensate for the imbalance. You need to know how much you need to change the colour weights to compensate for the indifference.
Lets take an example (rather basic one, but could be more complex i.e across multiple filters or environmental conditions i.e. light polution). You're using Astrodon 1:1:1 Tru-colour balance filters. As the moon rises it alters the light intensity of the blue filter, hence when you perform a colour combine of 1:1:1 ratios, your image has a blue shift. If you measure the background ADU of the blue channel and compare it to the R and G, it will be undoubtedly different and the cause of the issue. Now you can do one of two things, alter the weights to tone down the blue (of which you still need to measure the background level of the images to calculate the difference) or use pixel math to normalise all component image and continue to use the 1:1:1 ratios. The latter will give you the greater accuracy - in my experience.
Software like MaximDL performs an automatic normalisation function. I feel certain CCDSoft would have similar. Be careful using the automated functions if your image has nebulosity throughout i.e. there is technically no "real" background. In such cases, the best way of getting accurate colour images is to normalise manually. There is no free cut lunch if you want the accuracy - you need to work for the result.