Anomalous behavior on cropped photos

Troubleshooting and Bugs
1

I suspected something was wrong when I saw some extreme vignetting and very hard and color banding issues on specific shots where there is predominantly one color, like the sky. So far, I thought the problem was on my negative, light source, etc, but after inspecting the negative itself, and making some tests, I found the hard truth that NLP behaves completely different when the shot is cropped versus when the shot contains the film border.

I thought I was doing a good service on cropping and provding NLP just the “meat”, just the photographic information, but it seems to alter the curves in a worse way, than when compared to providing the whole scan (including film borders). I actually created a video to illustrate this better.

The issue persists both by pre-cropping and using the border buffer feature, I have roll analysis turned off and I am using version 3.1.1.

What should I do? I was suspecting that my presets and edits were very grainy because I was having to push sliders by a lot, and now I am suspeting that this is the reason, the curves are brutal.

Here’s the video I recorded to demonstrate the issue: https://youtu.be/SE2jH4H01xY

2

Welcome to the forum @35mm

NLP uses the information it finds in an image as shown on screen. The more info NLP can see regarding colours and tonality, the more likely it is that the conversion turns out in a way that can be used directly or as a good starting point.

Your “problem” image is no problem in itself, but it contains mostly a few hues of blue, low contrast and no relevant amount of green and red. Therefore, NLP has not much to wok with and still tries to give you something white and something black. Consequentially every little bit of vignetting is greatly amplified and colours turn out to be anything but acceptable in many cases. All of it is caused by NLP’s adaptive conversion and can therefore be considered to be normal.

In situations like these, roll analysis can help get you more suitable results. You can also sync settings from other images or include some of the space between the negatives. Including sprocket holes can help too. All these measures provide greater variety for NLP to work with.

Remember: NLP works with what it gets. The less it gets, the more surprises you’ll get.