Summary
First the main results. The SWIR photo (1500-1600nm) does seem more legible than the NIR photos. I did not keep as close an eye on exposure times as I wish I had, so there will be some variation due to unequal exposure, but I did my best to correct for that in post processing. It is very hard in any case given that the images were taken with different cameras and different types of camera even. In addition, the SWIR image is a panorama. By a procedure described below, it is possible to greatly improve the output of the SWIR camera though a "white frame subtraction." This was done on the SWIR images prior to building the panorama. The final output quality was only slightly inferior to the Sony A7S.

The large versions now follow, along with shooting details.
UV (Sony A7S, S8612 1.75mm + UG11 2mm, with a Convoy S2+ torch. F/16 ISO3200 10")

Visible (Sony A7S, BG38 2mm, halogen bulb, F/16 ISO320 0.25")

NIR 720nm long pass (Sony A7S, Hoya R72, halogen bulb, F/16 ISO250 0.25")

NIR 1000nm long pass (Sony A7S, unknown 1000nm eBay filter, halogen bulb, F/16 ISO2500 0.25")

SWIR 1500nm long pass (TriWave, Thorlabs FEL1500, halogen bulb, F/4, analog gain=1, 15fps, 405 lines of integration per frame, no gamma curve, digital gain=1, digital offset = 0, with dark frame subtraction on)
This is a panorama of 46 images stitched in Photoshop, then sharpened in Smart Deblur.

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Process for Construction of the SWIR Panorama
Next, I will discuss the process flow for the construction of the SWIR panorama. To begin with, a typical image from the camera looked like this (unprocessed in any way, original size):

Looking carefully, one can see there are a lot of artifacts, some from the sensor, some from a dichroic reflection (which I plan to take care of by finding a different filter attachment method eventually, and maybe a lens hood). My next step was to remove the dichroic reflection and the sensor glitches by taking a "white frame" and combining it with each image from the panorama in MATLAB. The white frame looked like this:

By fiddling in Photoshop, I discovered that inverting the white frame, doing a 50% opacity "Darker Color" blend in Layers, flattening the image, and adjusting the contrast would eliminate the ring. I then replicated this procedure in a MATLAB script and did it for every image in a batch. (I could probably have made a PS action to do this, but I chose not to, because I would rather keep my workflow in MATLAB as much as possible.) After this procedure, the image looks like this:

At this point all the images were combined into a panorama in Photoshop, and then it was sharpened in Smart Deblur.
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Conclusions
My conclusion is that the output image quality is acceptable, especially when tiled into a panorama with the white frame subtraction method. Here is a second, more dramatic example of the difference the white frame method makes, but on a different photographic subject:

This made such a difference to the final results that it will be used in all further work with this camera.
Edited by Andy Perrin, 26 May 2019 - 16:50.