Generative Quanta Color Imaging
Vishal Purohit Junjie Luo Yiheng Chi Qi Guo Stanley H. Chan Qiang Qiu
The astonishing development of single-photon cameras has created an
unprecedented opportunity for scientific and industrial imaging. However, the
high data throughput generated by these 1-bit sensors creates a significant
bottleneck for low-power applications. In this paper, we explore the
possibility of generating a color image from a single binary frame of a
single-photon camera. We evidently find this problem being particularly
difficult to standard colorization approaches due to the substantial degree of
exposure variation. The core innovation of our paper is an exposure synthesis
model framed under a neural ordinary differential equation (Neural ODE) that
allows us to generate a continuum of exposures from a single observation. This
innovation ensures consistent exposure in binary images that colorizers take
on, resulting in notably enhanced colorization. We demonstrate applications of
the method in single-image and burst colorization and show superior generative
performance over baselines. Project website can be found at
https://vishal-s-p.github.io/projects/2023/generative_quanta_color.html.