Ah ha, I understand what you meant now. And while I’ll agree that reducing the contrast will help you acquire the full range of the image more easily (possibly in a single exposure), isn’t a loss of contrast essentially the same as a loss of information? (It’s almost a tautological statement: we need multiple exposures to capture high-contrast images because there’s more information there than a 10- or 12-bit sensor can capture in one go.)
Outside of presenting the final results on HDR viewing equipment, I understand at some point in the processing chain (hopefully near the end) there is a “mix down” step where you convert to some 8-bit/SDR “window”, but in general it seems like the goal should be to maximize the available contrast/bit-depth available right up until that step.
This particular sensor has a couple 12-bit modes and a 16-bit raw mode for retrieving image data, but that’s just a description of the range of expressible values over the wire. I haven’t done any testing to see what sort of real dynamic range I’m getting from the sensor yet. Although, starting from one of Sony’s Gen3 Pregius models, I have high hopes. With a well depth of 20Ke-, in theory there should be somewhere in the vicinity of 14-bits to play with, but reality probably won’t be quite so kind.
We have direct evidence of this claim from the 1996 demo of Kodak’s “Vision” system in this RobinoScan post. The host mentions film grain (in the context of it being a negative thing that you want to minimize) several times starting at 5m30s and again at 8m30s. Reducing grain is one of the four major feature points they tout as the reason to switch to the new film stock!
My favorite app for this is made by the NeatLab folks. They already have best-in-class de-noising for still images in their Neat Image product. And then their Neat Video product adds a temporal component on top of that. Combine that with very attractive pricing and I’ve been using it to clean up digital sensor noise for years. I haven’t tried it with film grain yet, but I’m excited to see what it can do. The results usually feel a little like magic.
I agree that temporal denoising is one of the first and most important steps.
This is getting exciting now that a couple sub-systems are starting to come together. I just finished moving everything from my electronics/assembly bench over to my usual programming workstation. It’s time to get this software doing more interesting things!