Setting Global Exposure Using The Film Leader

Hi all, I have been experimenting with developing a best practices solution for setting the global exposure level of an entire roll of film based on spot metering the unexposed film leader (or what’s left of it). Has anyone had success using this method?

I’ve read several articles about setting the exposure for DSLR scanning, but surprisingly none of them seem to provide an accurate formula. Rather they give specific camera settings and fail to factor in that everyone’s light source will ultimately put out variable brightnesses that will affect the shutter speed for each individual setup.

I have also read on many forms that aperture priority mode should not be used, and that a single setting should be used for an entire film role. So it seems that people are ultimately measuring their entire role’s exposure level using the histogram of the first frame. What if that frame is under exposed? How can we know that that is the best reference to use for the exposure of all frames in the role? It seems to me like coming up with a formula based on the light coming through the unexposed leader of the film could be the most reliable method in establishing a baseline for the proper “mean exposure level” of the roll. Thoughts?

I found that DPL is fairly tolerant when negative film is camera scanned. I had tried it with bracketed shots taken from std. exposure to +3 EV using 1/3 EV increments.

I also took a bracketed series of just the backlight in order to see, how much I can overexpose without highlight clipping, and, decent colour rendering of bright areas.

My Canon EOS 5D Mark 3 reports a linearity limit which is at 10’000, about 1/3 stop below clipping.

I set my camera to UniWB In order to see where the non-linear part begins when I check exposure in live view. This Gives me the limit how far to the right I can expose.

I’ve also tried using the same exposure for the complete film but found no benefit of doing so. I think I’ll stick to manual exposure and ettr as outlined above.

Best hint I can give: Try it out with a film that has decent exposures as well as over- and underexposed images. You can learn more with a “difficult” film and see what you need to do in which case. “Easy” films can be good starters though.

Another thing I’ve experimented with is setting my exposure to where it just clips the the entire light source… so for instance, setup your light table (with no holder or film on top) and then adjust the shutter speed until your see the histogram clipping the entire light table.

In theory, you could then just keep that setting across different frames and even different film rolls. You will never clip the least dense area of the film emulsion, and I haven’t had a case yet were it clips the most dense areas (because the dynamic range of the film is so compressed in the emulsion that it easily fits within the dynamic range of the digital camera sensor).

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Yes, this is what I did (second paragraph in my post above) and found that this method works too. Again, NLP is fairly tolerant to exposure when scanning negatives. NLP can handle exposures from +0EV to +8/3 EV (almost three stops) with low contrast negatives:

This is one of the difficult images taken (in the late 70s) at night with mixed and very low light. The colours need some rework, but direct output (basic, linear flat, none) is fairly similar in the two shots that differ by almost 3 stops…
The righthand shot (taken at +8/3 EV) starts to get out of the sensor’s linear zone (I set RawDigger to show overexposure at 10’000)

Bildschirmfoto 2020-05-21 um 17.07.30

Nate, Digitizer thanks for the replies and thoughts! I will try that method on a roll. Got some film coming back tomorrow.

Thing is, I haven’t had a problem with clipping per say. I’ve noticed a slight difference in NLP’s interpretation of color and color contrast depending on the exposure. Although I suppose the precise location of the white balancing tool is also a variable in this. More research to be done. I do like your method for setting a baseline though.