# Improve old transparencies with Negative Lab Pro

**URL:** <https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983>\
**Category:** Guides and How-Tos\
**Created:** [November 30, 2020, 1:46pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983 "2020-11-30T13:46:49Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![Digitizer](https://avatars.discourse-cdn.com/v4/letter/d/57b2e6/32.png) [@Digitizer](https://forums.negativelabpro.com/u/Digitizer)\
**Post date:** [November 30, 2020, 1:46pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/1 "2020-11-30T13:46:49Z")

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I’ve just tried something.

I’ve inherited a load of transparencies that date back as far as 1950ct. Most of the older transparencies have shifted colours due to age, storage and whatever other causes might exist. I wanted to see if I can use NLP’s internal process to improve the overall appearance of the transparencies.

This is what I did

- changed orientation and cropped to taste
- adjusted WB and the RGB tone curve
- created a virtual copy
- inverted the RGB tone curve
- launched NLP

This is what I got:  
Left: Source image, Right: After using NLP

 ![test](https://canada1.discourse-cdn.com/flex029/uploads/negativelabpro/original/2X/1/1473e8558c3841f5f636787157966bc2b1a927f2.jpeg)

Both images were not customized other than what I listed above.  
Further improvements can be made with the HSL and Color Grading tools. Here’s a quick upgrade:

 ![Bildschirmfoto 2020-11-30 um 14.50.56](https://canada1.discourse-cdn.com/flex029/uploads/negativelabpro/original/2X/d/db4e8ba4e1b6ee6ef38848ffd717843a83ba9f91.jpeg)  
Sky: HSL tool was used to change the saturation.  
Grass: Color Grading was used.

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**Author:** ![Obj](https://avatars.discourse-cdn.com/v4/letter/o/e9a140/32.png) [@Obj](https://forums.negativelabpro.com/u/Obj)\
**Post date:** [December 12, 2020, 6:53pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/2 "2020-12-12T18:53:30Z")

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I logged in specifically to see whether NLP would be suitable for processing transparency scans. I’m currently embarking on digitising my late father’s vast archive, which consists of 2/3’s positives, 1/3 negatives. It’s good to know that NLP is a powerful tool for both.

BUT… wouldn’t it be great if it wasn’t necessary to invert the image first? If we could select a “transparency” option?

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**Author:** ![Digitizer](https://avatars.discourse-cdn.com/v4/letter/d/57b2e6/32.png) [@Digitizer](https://forums.negativelabpro.com/u/Digitizer)\
**Post date:** [December 12, 2020, 8:44pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/3 "2020-12-12T20:44:19Z")

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> [@Obj](#):
>
> wouldn’t it be great if it wasn’t necessary to invert the image first?

yes, sure, and I think that @nate is already looking into it 🖖

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**Author:** ![Obj](https://avatars.discourse-cdn.com/v4/letter/o/e9a140/32.png) [@Obj](https://forums.negativelabpro.com/u/Obj)\
**Post date:** [December 13, 2020, 2:27pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/4 "2020-12-13T14:27:28Z")

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That’s really good news. Thanks, Digitizer.

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**Author:** ![Digitizer](https://avatars.discourse-cdn.com/v4/letter/d/57b2e6/32.png) [@Digitizer](https://forums.negativelabpro.com/u/Digitizer)\
**Post date:** [December 13, 2020, 2:29pm UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/5 "2020-12-13T14:29:41Z")

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> [@Obj](#):
>
> really good news.

… beware, I was just guessing…

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**Author:** ![Fred\_EL2](https://avatars.discourse-cdn.com/v4/letter/f/ea666f/32.png) [@Fred\_EL2](https://forums.negativelabpro.com/u/Fred_EL2)\
**Post date:** [December 12, 2023, 3:19am UTC](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/6 "2023-12-12T03:19:03Z")

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Just wonder if there’s any other information or additional user insights into improving transparencies. I have many to do, and the task is very difficult.
