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[Sticky] What exactly does LNC or Local Normalization Correction and when do I change the default values to something else?  


Red Giant Customer
Joined: 4 years ago
Posts: 63
August 2, 2017 07:28  

Hi Mabula, 

I was always wondering when to use different LNC settings in the "Integrate" tab.

Can you explain to me what exactly it does and when to use different settings for it? 

There are tutorial videos around with 4th degree and 6 iterations and in one of your workflow tutorials you suggest 1st degree and 1 iteration. As far as my examples show I don't see a huge difference.

Thanks in advance 


Universe Admin
Joined: 4 years ago
Posts: 2662
August 2, 2017 21:02  

Hi Frank,

LNC stands for Local Normalization Correction.

It will correct the illumination in your frames in such a manner that the illumination differences of the separate frames in your stack will be matched locally instead of globally.

Normally, normalization is only corrected globally per frame. With LNC the gradients in  your data will be matched per frame while maintaining a solution for all frames at once that is stable and as flat as possible.

If you are combining data shot at 1 single night then LNC will still help, but the improvement is very little and visually hard to see, because locally the frames already match pretty well.

So if you are combining data with deviating gradients (multiple imaging sessions, data from different setups and/or photographers) then LNC should give a clear improvement.

An example: data of the Cocoon Nebula shot with a Nikon D5100 and a Robtics 102 ED apo. 2 frames shot at different nights with different moon fase and light pollution gradients and slightly different Field of Views. The effect of LNC is best seen on the borders where the stack artefacts are still visible.


Top row: neutralize background disabled in 5)NORMALIZE

Bottom row: neutralize background enabled in 5)NORMALIZE

Left: no LNC

Middle: LNC 1st degree 1 iteration

Right: LNC 4th degree 3 iterations

When to use which settings:

For regular integrations (I mean not a mosaic), start with 1st degree and 1 iteration. Then improve from there if needed. First increase iterations to 3. If that doesn't change the outcome, increase the degree. For regular integrations (no mosaics) normally 2nd or 4th degree with 3 iterations gives a very nice improvement.

For mosaics, it really depends on the data which degree and the amount of iterations that are needed. The user should experiment, but I recommend, just like for regular integrations, start with 1st degree and 1 iteration and then improve from there.


p.s. I have made this a sticky 😉