When posting about Image Conversion Issues, please include the following information:
Which version of Negative Lab Pro are you using? V3.0+
If using film scanner, please include: Epson V550, Epson Scan 2, Scanning as 48 bit Tiff @ 3200 dpi
Please add the conversion you are having difficulty with, along with a short description of what you are seeing wrong with it.
Hello all, I’ve been using NLP for the past three years and have found that I always have a rough time converting portrait photos shot in dimly lit rooms (particularly with darker skin tones). Here is the Raw Tiff Image:
I don’t see anything wrong with the scan coming from the scanner and was wondering if there was a way for the subject of the frame to really pop out from the background.I would love some guidance to see whether I have been doing things wrong post-process and to see whether I can get this image looking like the scans that I used to get from the lab shot in similar conditions. This is what the file looks like converting with no changes added (Linear Flat) as well as a prior lab scan that I received:
I know that since I am using a scanner that the image won’t come out as sharp but it would be great to figure out this issue to speed up workflow by a ton. Any advice is appreciated, thanks for the help in advance!
Comparing the two scans feels like comparing apples and oranges. The images have been taken under different conditions. The one you share is resisting conversion and needs some adjusting.
Thank you for replying @Digitizer! Yeah I understand that the two images won’t be exactly the same due to being shot in different lighting conditions but I do feel as though the initial conversion algorithm shouldn’t be as blue. Also with the edit that you attached, I noticed that the color of the subject’s beard is tinted brown for some reason as well as the jacket being tinted purple when it should be pure black. I’ve ran into this issue before when shooting in a room where the background is primarily black but haven’t been able to find a way around it. I’m wondering if you might have any tips as well @nate? Any pointers would be greatly appreciated!
I also have another image from the roll in the same room where you can see there is a strong blue/green tint and the subject’s skin tones are being muted:
Oh, and I also increased the “Border Buffer” during conversion because it looks like you either have some extreme vignetting or light issues in the top right corner of the frame, and I didn’t want than to be considered in the analysis.
And also, I made some final adjustments to the shadows:
It is a common knowledge that NLP works best when the negative have many colors and tonal ranges. If this is not true, the heuristics which guides conversion does not work. To get a sense what I am talking about take the digital photo shot in the same condition - flash lighting at night with only foreground properly exposed and deep shadows in the background. Convert this picture into negative using any means and save as dng or 16 bit tiffs. Now give this converted negative to NLP and see the results. I am betting you will encounter the same issues you describe in your post. Then see what you need to convert negative back to look like original. That exercise should demonstrate what NLP can and cannot do.
