Getting grass color right

This photograph was taken in 1984 using Kodak Gold 100 film.
I scanned a print (developed in 1984) recently using an Epson V370 scanner (first image below)
I have also digitized the negative with an Olympus EM1 Mark iii camera (60mm macro lens, Kaiser Light panel) and converted with Negative Lab Pro (V 2.2 Kodak setting). - second image

The Olympus/NegLabs Pro image taken from the negative has much yellower grass than the Epson Scan of the print (where the grass is much greener. I have tried adjusting the colors after conversion (the RGB sliders in NLP) and can get the grass color the same, but not the skin color at the same time.

One thought. I believe that the cameras sensor has two green photosites for each red and blue one in order to correctly interpret colors in a positive image (or real life). Does this cause difficulty when recording a negative image?

…not really…and if it did, all greens would turn out as yellow as in your example. I expect that different settings in NLP will bring back that green green grass of home.

Can you share the original shot for us to try? You can use cloud drives or sharing platforms to this end.

Thanks for the offer.
Ill give it a go. Its a large file as I scanned the negative in High Res mode (80MP)…
What email should I link to?

You can link to

Ive emailed you a onedrive link. Let me know if it works…
. I have a number of pictures taken of the same subject on the same day with the same film which I am very fond of, so hopefully can sort out some settings which will work for them.
Many thanks for offering to help

Got a fail to deliver to this email. do you have another email I can try?

Try to send the image file(s) over 80 MB attachments almost never make it over direct eMail… Or use google drive or iCloud or…

I’ve think Ive managed to send a link to Nates email ( Hope thats OK?

oops, the alias that I had created seems to have been lost. Please resend the link to

Ive had another go, seems to have gone through this time. Let me know if it doesn’t work.

Try the Fuji colour rendering. Fuji film is best known for its greens.

You can always tweak the colours in a tiff-export…

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Many Thanks. Still getting to grips with teaking RGB curves/colors…

The film scan looks far more accurate. Note the magenta skin tones, blue cast in the dress, and blue shift in the grass, all in the scan of the print.

Yes, I think the negative scan converted with NLP (Fuji color and settings thanks to digitizer) is nicer than the scan of the print. Some more fiddling around resulted in the attached (including grain reduction with Neat Image)

Interesting that the “fuji” color balance works with a Kodak Gold 100 film?

What time of the year was the photo taken. The images would be very dependent on the climatic conditions.

The Photo was taken at a garden party just after the exams in Cambridge University in June 1985

I think it had been relatively dry and sunny during our exams (one always remembers ones youth as gloriously sunny!) which might account for the yellower color of the grass?

One thought. I have not found specs for the Keiser light source but am guessing that it uses white LED’s. I would love to see a scan of the same negative using a phone or an iPad for your backlight. They have no white LED’s but make white with individual red green and blue sites all on together. Cameras see red way into the orange of the film’s orange mask. But the paper that made your print is blind to that orange (you would use an orange safelight). RGB light sources eliminate some of this confusion by narrowing the effective red sensitivity of the camera. Nate Weatherly has written much about this.

…you’d want a phone with an OLED display, only these have r, g and b light emitters. The more common LC displays use filters and white backlights.

Please be so kind and add a link to what Nate Weatherly has written about.

WRT the iPad, thanks for the clarification. The red filters on old iPads may not be narrow enough to be effective here.

There is a wealth of information on this topic on the site and specifically this link: Nate Weatherly’s comments.