NLP Inverted Copies are significantly larger than original scans?

Hi Forum, not sure if this is quite the right category to post in, so please let me know!

I don’t think this is a bug or an issue with NLP – I’m just curious about the behavior. I scanned a bunch of B&W negatives and inverted them in NLP. The scanned TIFFs are around 28 MB at 3200 dpi. After saving a positive copy of the tiff for further edits, I noticed that the positive copies are nearly 3x the size at ~80MB.

Neither my scanner’s tiffs nor the NLP copies are compressed, so it’s not something on that front.

For a little more context, my workflow is kinda cursed in that I scan the negative, pull it into Lightroom Classic, do the NLP inversion, save the positive tiff in a subfolder, and then pull that subfolder into Lightroom CC for final edits. I usually end up deleting the original scans and keep the inversions on hand. So obviously saving space would be nice and so would eliminating Lightroom CC from the workflow. I know that I can sync Lightroom Classic photos to the CC library, but because the curves and things on the inversions are off the negative, I find it difficult to edit further. And now I’m going off topic!

Anyway, why are the NLP positive copies so much larger than scanned negatives?

There are a few possibilities for a change of size:

  • different bit depth per colour
  • compression
  • colour matrix demosaicing
  • preview size
  • combinations of the above

I tested with tiff source files and found that the converted files have similar sizes.

I’m new to NLP but at a guess, your scan is RAW on conversion in Lightroom. Saving to TIFF always results in a substantial increase in file size. The question should be not why are TIFF files so big, but why raw files are so small compared to a normal sized image.

The TIFF file is the “normal size” image because it is in the form we can use it for viewing and printing. It’s got all 3 RGB channels, uncompressed. It is ready to view and print. It is stored in a common bit depth (8 or 16 bits per channel) Other programs can use it straight away.

Being raw, the raw file is not so normal. It only has one channel so it is not recognizable as an image by human eyes, it is stored at 10 or 12 bits, it probably has lossless compression, for those three reasons its file size is smaller than a normal image.

My scans from my scanner are Tiff files at 16-bit greyscale. I forgot to mention the case I described yesterday was b&w. I should see if NLP saves the Tiff with more greyscale bit depth somehow.

RAW does not enter my workflow at any point. I deal exclusively with Tiffs for originals.

Okay, if your scans are scanned as greyscale, they have a “gray” colour space. NLP exports come in “rgb” colour space…

I’ve converted the one (and only) “gray” scan I found and it came out to be 10 times the original size.

Sticking to the gray colour space saves some space… but a few apps out there cannot handle such files. When I convert the file manually and export it as DNG, the size of the DNG is as small as the original file.

Note: “Gray” scans can be recognised by a few of Lr’s sliders: They are grayed out.

@Digitizer it’s the RGB colorspace indeed! Thank you for pointing it out, I have confirmed on my end and setup a photoshop batch action to revert them to 16-bit greyscale. It’s nice to reduce the file size of my 4x5 scans haha