***Update*** The version used in this video was Version3. Version4 is now available for download as I had to make a modification to the HOO process.
Narrowband Normalization is a pixelmath process I came up with to help you equalize your narrowband data with a simple drag and drop operation for both SHO and HOO images. I feel the best results do come from non-linear data as I illustrated in this video but feel free to test this on your end. For the HOO math, I am using a method that Luke Newbould came up with that he uses for his OSC image processing to help make your OIII signal pop thus making your image look like a “Hubble Pallet” style image. Thanks Luke, for testing this math and giving it your approval! Below are the download links to all the pixelmaths I used in this video. I also want to put another special thanks out there to James Lamb for coming up with the Modified SCNR math and allowing me to put out my version of it out there for you all to use. I welcome your comments so please don’t hold back. Thanks!!!
Lukomatic Youtube Channel: https://www.youtube.com/c/lukomatico
Luke’s OSC processing video:
https://www.youtube.com/watch?v=QV6ObLVRvNk&t=989s
James Lamb YouTube Channel: https://www.youtube.com/user/Aero19612
James Lamb Modified SCNR video:
https://www.youtube.com/watch?v=YGMRn-fMVV8
My maths used in this video.....
Narrowband Normalization PixelMath:
https://drive.google.com/drive/folders/1dSZzimxsnAPpqTkEJO5pzt1gqSahMUyO?usp=sharing
Stretching PixelMath:
https://drive.google.com/drive/folders/1ZuE8VKlrryofFAGdx-hIH8drrdNZxVCN?usp=sharing
Star Reduction PixelMath:
https://drive.google.com/drive/folders/1qjJFliMgSoPUe3zaPG5NeXyIDNR_RQ4Z?usp=sharing
RGB Stars to Narrowband Transfer PixelMath:
https://drive.google.com/drive/folders/15zRH1p2Xn2ReUJj7bNVCFGQ1yA_JuNnJ?usp=sharing
Modified SCNR PixelMath link:
https://drive.google.com/drive/folders/1aoD8NGH6Tt6m0c2hNyPVQ5j-bONpXlUI?usp=sharing
Color Masks PixelMath:
https://drive.google.com/drive/folders/1HOU2zqRfqArDtKPQiq67_q-JcZWnq2lK?usp=sharing