NLP colour pipeline / image operators / ICC profile handling

Hi there NLP fans, I too enjoyed testing NLP especially for colour work and bought a license.

Yet after some more detailed testing I’m hesitant to commit to using NLP for monochrome scans. I give the context (this will be a tad technical) and the questions one by one:

  1. A clean starting point
    When first converting a negative, NLP appears to add a mild gamma transform. Even if I select “LINEAR” and/or adjust the Clipping operators a gamma shift occurs and the black and white points move. But if I invert manually using LR’s curve palette no shift occurs. Ok so why does this trouble me?

I’ve heard many people like to use NLP to create Positive DNGs and work from them (and use the LR operators ‘non-inverted’) but it concerns me that I can’t get a ‘pure’ inversion of my original without an unknown gamma shift being burnt into my DNGs. It means I can’t go 100% back to my original scan…

Resulting questions:

  • Is there any way to get a 100% pure inversion as a starting point with NLP?
  • Or else to work with images that I have inverted myself?
  • A monochrome scan tagged as sGray changes to either ProPhoto/sRGB/Adobe etc profiles when converted to a Positive in NLP - how to invert and keep it as sGray?
  1. It’s challenging to create masks in LR and work with the LR operators operating in ‘reverse’. I profiled NLP’s operators (“Contrast” etc) and most of them function pretty similarly to LR’s own operators (‘Exposure’ is a Gain operator, ‘Contrast’ is an S-Curve etc) one nice exception is ‘Brightness’ in NLP which appears to be a Gamma operator.

Resulting question:

  • Similar to before, how can I work with NLP operators but also use the LR operators ‘normally’? I’m pretty sure that whilst LR’s operators such as “Highlight” and “Shadow” might appear to function the same when inverted (Highlight becoming Shadow etc) - they are in fact optimised to work on positive image data.

I’m sorry if that’s a lot of questions and maybe I am missing something obvious but If I can’t figure the workflow out - it’ll be a pity to only use NLP for colour whilst relying on LR’s built-in tools to achieve the tonal distribution I need manually from a scan I inverted myself and tagged as sGray :slight_smile:

Thanks for reading and any pointers anyone might have.

Hi, as of v3, you can now choose whatever default settings you would like for black and white conversions.

After installation, the pre-programed default is called “NLP Standard - B+W”, which include a gamma curve that is meant replicate the curve properties of black and white photo paper.

You should not see any colors - it should be pure black and white. If you do see colors, make sure that you selected “B+W” as the ColorModel before converting.

Changing the ToneProfile to “linear” will give you a linear curve. To make this “100% pure” without any points in-between, go to the “Advanced Tab”, set the “Curve Points” to “Manual”, and then set it to just 2 points. Just note if you do this, most of the adjustments in NLP will not work - it will just adjust those two points - the black point and the white point.

Any files that go into Lightroom are edited in MelissaRGB (ProPhoto primaries and sRGB gamma curve). I don’t know if there is a way in Lightroom to export out to sGray directly, but the closest thing would be sRGB.

Yes, most LR operators all are working against the original image data (the negative). So they will respond non-intuitively. I have more info about optimizing integration with Lightroom here: Lightroom Tips & Tricks | Negative Lab Pro


Hi Nate, thank you so much for taking the time to reply personally, really appreciate it! :pray:

Ok so NLP Standard - B+W by default applies an output gamma correction to try to mimic a rendering that would sometimes applied through printing to black and white paper - ok but then I would love to know what input gamma is NLP assuming the image data is stored in? Isn’t it that for really accurate results the output gamma that is applied should make sense relative to the input gamma.

Thanks also for the tip with the 2 points. I will try this and hopefully I can get a perfectly reversible inversion from Negative to Positive using NLP. But then as you say I will have the problem that with only 2 points I can’t use most of the operators.

Following from that question - is there a way to get NLP to “own” and operate on a Positive file that it didn’t generate? (So make it work as “Positive Lab Pro” :slight_smile:

And lastly with my ICC profile question - I asked because if I merge 2 panoramic Greyscale scans tagged as sGray using LightRoom it creates a new file that preserves the Greyscale+sRGB properties.

But when I create a new ‘Positive’ file from a Greyscale source using NLP I can’t seem to get the new file to preserve the properties of the negative original.

Once again - huge thanks for your help and taking the time to answer.