Author Topic: Processing filtered Ha through a DSLR  (Read 2900 times)

Offline Jfakatselis

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Processing filtered Ha through a DSLR
« on: 2014 November 29 09:03:20 »
What would the recommended process be for processing a set of Ha images taken with a NB Ha filter via a DSLR?
Wanted to combine these with the RGB image.

Should I use the BPP script as normal with RGB images then extract the red component?
Should I extract the Red Channel first then try using the BPP script?
Should I run Batch Channel Extraction first?

There could be several options, which one would be the optimal?

Thanks,
Jim


Offline lensman57

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Re: Processing filtered Ha through a DSLR
« Reply #1 on: 2014 November 29 10:51:18 »
Hi,

Use BPP with all the relevant calibration frames loaded but set to calibrate only and set the Debayer to SuperPixel.
Use the Channel Extraction script to only save the R channel and discard the G&B.
Use the Star alignment tool to register the R subs to each other and then use the Image Integration tool to combine.
You end up with a mono ha image.

Regards,

A.G

Offline pfile

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Re: Processing filtered Ha through a DSLR
« Reply #2 on: 2014 November 29 10:55:27 »
there are so many ways to skin this cat... the most straightforward is what you describe first.

there are lots of variants on the 2nd/3rd option. one would be to use superpixel debayering on all the subexposures (bias, dark, flat, light), then extract the red channel from each of them and throw away the others. now you've got files that are as though they came from a mono camera. so you just put all those single-channel files into BPP and go from there.

if you don't want to use superpixel debayering, then you could use BPP to calibrate the raw images, then run ChannelExtraction on the calibrated lights, then put those single-channel files into BPP.

the advantage is mostly just that you will save a lot of disk space and the runtime for the whole mess should be shorter, as PI only deals with 1/3 of the data. but the results in all 3 cases will probably be the same.

rob