Getting strong green or purple color cast from batch-converting old color negatives

Hey everyone, I’ve looked through the help section of the website and the forum and couldn’t quite find something that could help me so here I am.

I’m DSLR-scanning a large amount of “old” (1990s) color negatives. I obviously batch-convert them to save time but some of them come out ok and some of them come out with a very high contrast and very strong purple or green color cast:

My setup: Sony A7R2 + Sigma 105mm f/2.8 macro lens + Cinestill CS-lite as a light source. Shooting RAW files.
It works well with black and white negatives but I’m going crazy with the color ones… I can’t edit them one by one, I really don’t have the time.

Could someone please help?
Thank you in advance.

Welcome to the forum @MichaWha

Hard to say what’'s going on with your conversions.

If you could share an unedited raw file or two, we could try our luck.

For starters, you can do a few things

  • verify that the highlights aren’t blown in your scans and if you
  • converted the image(s) more than once without un-converting in-between.
  • Sometimes, it helps to use very low pre-saturation.

Thanks for the reply.

Here you go: https://drive.google.com/file/d/1-1EBtCai1WqhttpvIMoiMH3qwQgFNb9t/view?usp=sharing

When I scan, I always look at the histogram and keep it as close to the bright side as possible without being overexposed.

I simply batch-convert once. Though I’m having something weird: I batch-convert let’s say a hundred scans, when it’s done I click “apply” and nothing happens. I have to open NLP again and click “apply” once more to see the changes. Maybe that’s the source of the problem but how do I make it work without starting NLP twice? It never did this with B&W negatives.

I already use the lowest pre-saturation settings.

By the way I’m using Lightroom Classic and NLP 3.0.2

On my iMac and with LrC 13.4, I tried a few things, but let’s first mention the following

  • The negative has low contrast and the histogram is all cramped at the right side.
    NLP’s conversions can pick up almost any cast or strange colours with thin negatives.
  • Colour variety is small. Just green and pink (I exaggerate to make it more obvious)
    NLP can deliver more balanced output with greater colour variety.

Low contrast as seen in RawDigger:

Okay, let’s have a look:


Left to right:

  • Negative
  • Converted with NLP 3.0.2 (Noritsu. PS=1, Defaults)
  • Manual conversion to find out, whether there is enough data for “better” results

And this is what NLP 3.0.2 can do with a little bit help from a friend:

In this case, the friend was Lightroom’s automatic WB & tone control in the Library tab.

Lessons learned:

  • don’t overdo ETTR
  • If it doesn’t match your expectations: Ask (you did) and Try a few things e.g.
    • use a different WB
    • play with LrC tonality settings
    • play with NLP sliders, colour models etc.

Hope that helps.

Thank you very much for looking into it!
In the meantime I also tried to lower the exposure when scanning in order to have more colors and contrast on the negative instead of having the histogram cramped to the bright side. I’ve also tried using the “blue light” on the CS-Lite (it has 3 settings : “orange light” mostly used for slide film, white light and “blue light” mostly used for negatives and until now I was only using the white light).
And it seems to work a LOT better, I only get a few shots with odd colors in large batches so that’s fine to me!

But I’m still having the problem where once the batch-conversion is finished, nothing changes (the negatives still show up as unconverted). I’m wasting quite some time with this as I don’t really understand what’s going on, it wasn’t doing that when I was batch-converting hundreds of BW negatives at once. Do you have any idea?

Thank you again.

I see that in Lightroom, when I convert in the Develop module. Neither the preview nor the thumbnails in the film strip change - until I hit Apply. In Library module, things move differently and I do my conversions there for that reason and in most cases anyways.

Changing settings or pressing buttons in rapid succession seems to cause occasional issues too. When I have NLP convert bigger batches, I usually let it sit for a second or two before proceeding. This feels strange in days of high power processors, multithreading etc., but it helps to prevent hiccups. Conversion results aren’t touched by this though.

I always convert in the library module and I always wait a few seconds at each step to let my computer do its thing but really, it still doesn’t work the first time. With the last batch it didn’t work at all, I had to unconvert all the negatives (approx. 200) and reconvert them in smaller batches…