First of all, I love NLP and can’t wait to use it more. Thanks Nate!
I’m relatively new to NLP, but recently I have been using it quite frequently for both color and B+W projects. I took note of the fact that Nate suggested to “expose to the right” (ETTR) when camera scanning negatives.
I understand the idea of ETTR when using a digital camera on a physical scene, but my head starts hurting when I think of it in relation to shooting a negative that will then be inverted.
In the projects I have done so far, it seemed to benefit color negatives, but not so much with B+W negs. When camera scanning a B+W neg, when you nudge the histogram to the right, you are creating a lighter negative that will be inverted to a darker positive. I end up with NLP images that seem too dark to start and I need to raise the lights and whites almost all the way to get the image to look right.
I noticed in the recent camera scanning tutorial video from Darryl Carey, he didn’t mention ETTR at all. Can anyone set me straight here with what I am missing, or what your preferred exposure technique is. Thank you.
NOTE: I’m super-new to this so don’t take anything I say as The Truth. If I am incorrect please let me know as I’m here to learn as well. Thanks!
I’m not an expert on this, but I think the idea is to retain shadow detail in the final image.
Digital cameras struggle with highlight details, while film struggles with shadow. By exposing to the right on the negative scan you are capturing the most data possible in the highlights (where most of the information is in a digital image) which will end up preserving detail in the shadows of the positive.
So it’s not about exposure, but detail retention in the shadows. Whenn ETTR in digital you generally have to stop down in post to get the final image looking good. For positives from negatives will be the opposite - which is what you are seeing with your images coming out darker than you’d expect.
Note: Why ETTR is used for digital (from Wikipedia):
*" Their rationale was based on the linearity of CCD sensors, whereby the electric charge accumulated by each subpixel is proportional to the amount of light it is exposed to (plus electronic noise). *
Although a camera may have a dynamic range of 5 or more stops, when image data is recorded digitally the highest (brightest) stop uses fully half of the discrete tonal values.
This is because a difference of 1 stop represents a doubling or halving of exposure. The next highest stop uses half of the remaining values, the next uses half of what is left and so on, such that the lowest stop uses only a small fraction of the tonal values available.
This may result in a loss of tonal detail in the dark areas of a photograph and posterization during post-production. By deliberately exposing to the right and then stopping down afterwards (during processing) the maximum amount of information is retained."
Sounds about right Cliff, but you’ve got your final highlights and shadows swapped.
ETTR improves shadow noise on digital cameras by increasing the SNR of the entire digital capture (thus including the shadows, and assuming the DR of the scene allows you to increase exposure without clipping). In a digital capture of a film negative, what’s in the shadows? The scene’s highlights! So digital ETTR captures of film negatives actually reduce noise in your final image’s highlights.
Interestingly, the commonly held belief that ETTR works by increasing the number of discreet tones available is, while harmless, incorrect. This paper explains it well: “The number of available raw levels has little to do with the proper reason to expose right, since as we have seen the noise rises with signal and in fact the many raw levels available in higher exposure zones are largely wasted in digitizing photon shot noise” (from the “S/N and Exposure Decisions” section)