Quantitative and dark field ghost imaging with ultraviolet light

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 thermo...

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Bibliographic Details
Published inarXiv.org
Main Authors Song, Jiaqi, Liu, Baolei, Wang, Yao, Chen, Chaohao, Shan, Xuchen, Zhong, Xiaolan, Ling-An, Wu, Wang, Fan
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 02.08.2023
Subjects
Cooling systems
Ghosts
Hyperspectral imaging
Image reconstruction
Imaging techniques
Phase objects
Quantum efficiency
Sun screens
Thermoelectric cooling
Ultraviolet radiation
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Summary: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.
ISSN:2331-8422