  In this work, we present a camera configuration for acquiring "stereoscopic
dark flash" images: a simultaneous stereo pair in which one camera is a
conventional RGB sensor, but the other camera is sensitive to near-infrared and
near-ultraviolet instead of R and B. When paired with a "dark" flash (i.e., one
having near-infrared and near-ultraviolet light, but no visible light) this
camera allows us to capture the two images in a flash/no-flash image pair at
the same time, all while not disturbing any human subjects or onlookers with a
dazzling visible flash. We present a hardware prototype of this camera that
approximates an idealized camera, and we present an imaging procedure that let
us acquire dark flash stereo pairs that closely resemble those we would get
from that idealized camera. We then present a technique for fusing these stereo
pairs, first by performing registration and warping, and then by using recent
advances in hyperspectral image fusion and deep learning to produce a final
image. Because our camera configuration and our data acquisition process allow
us to capture true low-noise long exposure RGB images alongside our dark flash
stereo pairs, our learned model can be trained end-to-end to produce a fused
image that retains the color and tone of a real RGB image while having the
low-noise properties of a flash image.
