  Ultraviolet (UV) imaging enables a diverse array of applications, such as
material composition analysis, biological fluorescence imaging, and detecting
defects in semiconductor manufacturing. However, scientific-grade UV cameras
with high quantum efficiency are expensive and include a complex thermoelectric
cooling system. Here, we demonstrate a UV computational ghost imaging (UV-CGI)
method to provide a cost-effective UV imaging and detection strategy. By
applying spatial-temporal illumination patterns and using a 325 nm laser
source, a single-pixel detector is enough to reconstruct the images of objects.
To demonstrate its capability for quantitative detection, we use UV-CGI to
distinguish four UV-sensitive sunscreen areas with different densities on a
sample. Furthermore, we demonstrate dark field UV-CGI in both transmission and
reflection schemes. By only collecting the scattered light from objects, we can
detect the edges of pure phase objects and small scratches on a compact disc.
Our results showcase a feasible low-cost solution for non-destructive UV
imaging and detection. By combining it with other imaging techniques, such as
hyperspectral imaging or time-resolved imaging, a compact and versatile UV
computational imaging platform may be realized for future applications.
