Stereoscopic Dark Flash for Low-light Photography

• Published in: IEEE International Conference on Computational Photography pp. 1 - 10
• Main Authors: Jian Wang, Tianfan Xue, Barron, Jonathan T., Chen, Jiawen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2019
• Subjects: Cameras; computational photography; dark flash; Image color analysis; low-light imaging; Mobile handsets; Photography; Sensitivity; stereo
• ISSN: 2472-7636
• DOI: 10.1109/ICCPHOT.2019.8747337

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 wavelengths instead of red and blue. When paired with a "dark" flash (i.e., one emitting near-infrared and near-ultraviolet light, but no visible light) this camera allows us to capture a flash/no-flash image pair at the same time, all without 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 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.