Computational and dark-field ghost imaging with ultraviolet light
Jiaqi Song, Baolei Liu, Yao Wang, Chaohao Chen, Xuchen Shan, Xiaolan Zhong, Ling-An Wu, Fan Wang
Abstract
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 complex thermoelectric cooling systems. 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. 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 nondestructive 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.