So I just started using NLP this week - loving it so far! I just wanted to ask what the best method and workflow is for Flextight scans.
Here’s what I do:
Scan negatives as 3F format.
Rename files from .fff to .tif
Import to Lightroom and use Tiff Prep option (using Flextight MAC).
Convert negatives without any form of cropping or white balancing
Is this the correct way or am I missing out on something? The colors are usually pretty good, but always in need of some tweaking. I’ve seen some conversions which look really nice with basically one click conversions.
This made me wonder if there is a way to convert with better accuracy. I read that you can leave some of the orange mask in before converting, but what about the completely blank areas outside of the actual film area? Will that throw off the color analysis?
I also am wondering about this. I have the exact same workflow as Thomas, but my results always look off. I have better results skipping the TIFF prep and converting as I would from a flatbed - but have assumed I’m missing something. Any help here would be appreciated.
Crop
According to the NLP manual, the scans should be cropped in a way to hide the unexposed film base/borders. I often convert negatives without cropping and then set border buffer to 25% which can also get me better initial conversions with underexposed negatives. NLP looks for the “white” and “black” points in each of the r, g and b tone curves. Leaving blank areas will push NLP on a false track - unless you increase the border buffer. If the negative includes large areas of high density, it can help to set a crop to exclude those areas (e.g. overexposed skies)
White balance
I find that NLP is fairly tolerant to white balance and that wb can change the initial conversion nevertheless. AutoWB can help too.
