Tri-Color Narrow Band RGB DSLR scanning

[Chromium VI]

Darktable has a builtin de-Bayering option. If activated (under the demosaic menu) a 4x larger image will result.

 

[loccdor]

It would be relatively trivial for a programmer with an image processing package to be able to combine the R G B of 3 images. I had Gemini write one real quick for Python.

from PIL import Image
import os

def combine_channels():
# Define filenames
r_path = 'red.tif'
g_path = 'green.tif'
b_path = 'blue.tif'
output_path = 'rgb.tif'

# Check if all files exist to avoid errors
for file in [r_path, g_path, b_path]:
if not os.path.exists(file):
print(f"Error: Could not find {file} in the current folder.")
return

try:
# Open the source images and convert to grayscale (L mode)
# just in case they aren't already formatted correctly
r = Image.open(r_path).convert('L')
g = Image.open(g_path).convert('L')
b = Image.open(b_path).convert('L')

# Merge the three images into one RGB image
rgb_image = Image.merge('RGB', (r, g, b))

# Save the result
rgb_image.save(output_path)
print(f"Success! Saved combined image as {output_path}")

except Exception as e:
print(f"An error occurred: {e}")

if __name__ == "__main__":
combine_channels()

 

[brbo]

As far as I know, Grain2Pixel plugin has support for separate R G B scans.

 

[silvergelatin]

The big scanlight is actually quite deep compared to other lights I have seen. 5cm roughly. I believe it was designed this way specifically to eliminate poor light mixing. Jack said that it could maybe be caused by IR light reflecting off the lens or holder, but when taking these sample images I had the camera well away from the light source such that any reflection would be negligible.

Maybe it is a faulty device. One other user on the NLP forum told me they saw a similar effect which was reduced by lifting the film plane farther from the surface of the light. I purchased some NR glass to elevate the holder a bit, but it has yet to arrive.

I have the same issue with my Big Scanlight. Jack told me it is likely caused by internal IR reflections in the lens as well. In actual practice this isn’t an issue unless the neg is extremely underexposed, but it still bothers me. Otherwise, this light is the biggest upgrade in color image quality I have made to my system. My Ektar scans actually look like slide film now.

 

[originalwinslow]

I have the same issue with my Big Scanlight. Jack told me it is likely caused by internal IR reflections in the lens as well. In actual practice this isn’t an issue unless the neg is extremely underexposed, but it still bothers me. Otherwise, this light is the biggest upgrade in color image quality I have made to my system. My Ektar scans actually look like slide film now.

I find that it is present even in thick negatives, albeit nearly unnoticeable until you apply a correction via FFC or radial mask and compare the difference. I have found that a radial mask is effective enough at eliminating it without introducing major color shifts but it requires some tweaking to balance correctly. Faster and easier than batch FFC, particularly in lightroom.

I got some NR glass but am only able to easily elevate the film plane around .5cm which does not reduce the vignette whatsoever. I need to figure out a way to elevate it further but that may be more trouble than it's worth.

I have also noticed an increased prevalence of magenta in the shadows vs white light that needs to be corrected for. This can be quite frustrating and throw off the color balance of the image. In some cases I cannot fully eliminate it at all.

 

[silvergelatin]

How are you creating the radial mask, and does it account for the color difference?

I have not had an issue with magenta shadows. Are you using NLP, or doing manual inversion in PS?

Also, what camera and lens are you using?

 

[originalwinslow]

How are you creating the radial mask, and does it account for the color difference?

I shot a blank frame of just the light surface and adjusted size, feathering, exposure and tint to compensate for the vignette as best as possible. I have found that adding the mask after NLP conversion looks a bit better.

I have not had an issue with magenta shadows. Are you using NLP, or doing manual inversion in PS?

NLP for almost everything. I am going to try some other automatic conversion tools and compare. Notably Capture One just released built in negative conversion.

Also, what camera and lens are you using?

Nikon D810 w/ 60mm 2.8D micro

 

[silvergelatin]

I shot a blank frame of just the light surface and adjusted size, feathering, exposure and tint to compensate for the vignette as best as possible. I have found that adding the mask after NLP conversion looks a bit better.



NLP for almost everything. I am going to try some other automatic conversion tools and compare. Notably Capture One just released built in negative conversion.

Nikon D810 w/ 60mm 2.8D micro

I find that NLP requires quite a bit of manual white balance with the RGB light compared to flash. It does easily snap into place for me, though.

Have you tried negating the orange mask using the RGB controls on the light and then manually inverting? This has worked well for me.

 

[originalwinslow]

I find that NLP requires quite a bit of manual white balance with the RGB light compared to flash. It does easily snap into place for me, though.

Yes, there seems to always be an excessive magenta cast that is usually easily corrected with a few clicks on the tint slider. However, the shadows sometimes remain problematic in my case.

Have you tried negating the orange mask using the RGB controls on the light and then manually inverting? This has worked well for me.

I have not fiddled too much with balancing the individual luminance on each channel, but I do find that skipping white balancing the mask in LR gives a better result. Specifically reducing the tendency for over saturation of greens and reds.

What adjustments work for you to get the mask balanced? Does this also benefit the conversion via NLP? I found that NLP basically overrides the individual adjustments and gives me the same result unless the luminance levels of a certain channel are heavily reduced. Then things get wonky.

 

[silvergelatin]

Yes, there seems to always be an excessive magenta cast that is usually easily corrected with a few clicks on the tint slider. However, the shadows sometimes remain problematic in my case.

I have not fiddled too much with balancing the individual luminance on each channel, but I do find that skipping white balancing the mask in LR gives a better result. Specifically reducing the tendency for over saturation of greens and reds.

What adjustments work for you to get the mask balanced? Does this also benefit the conversion via NLP? I found that NLP basically overrides the individual adjustments and gives me the same result unless the luminance levels of a certain channel are heavily reduced. Then things get wonky.

It varies by film, but for Ektar, I reduce red a little to 190, leave green all the way up, and blue goes way down to 95. This gives me a nearly perfectly gray base. I can simply invert and the color needs very little tweaking.

You’re right, though - with NLP it doesn’t really matter. It makes a bigger difference with manual inversion.