# Color in center and edge

**URL:** <https://forums.negativelabpro.com/t/color-in-center-and-edge/7599>\
**Category:** Digital Camera Scanning\
**Created:** [March 24, 2024, 9:15am UTC](https://forums.negativelabpro.com/t/color-in-center-and-edge/7599 "2024-03-24T09:15:06Z")\
**Posts on this page:** 1\
**Showing post:** 9

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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:** [March 26, 2024, 10:59am UTC](https://forums.negativelabpro.com/t/color-in-center-and-edge/7599/9 "2024-03-26T10:59:15Z")

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> [@Wilfried](#):
>
> So my conclusion is, old film could be difficult to handle.

Old film can be difficult to handle and I tried NLP with transparencies that are about 70 years old…with fairly good results:

> [@Improve old transparencies with Negative Lab Pro](https://forums.negativelabpro.com/t/improve-old-transparencies-with-negative-lab-pro/2983/1):
>
> 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…

As for negatives, most of the films I convert are between 30 and 50 years old and most of them convert fairly well. Overexposed or thin (underexposed) negatives are more difficult to convert, but results can be improved if e.g. the overexposed (“blown”) parts are excluded from NLP’s analysis - by cropping said parts off before converting. It takes a bit of time and exercise to find out, when and what crop to apply though.

I mostly set “Border Buffer” to something between 15% and 25%, also in order to not have to crop before converting, and in order to focus NLP on the “important” central parts of the images.

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