Giga-voxel multispectral time-resolved imaging with single-pixel detection and data fusion

被引：0

作者：

Lenz, Armin J. M. ^{[1
]}

Soldevila, Fernando ^{[2
]}

Ghezzi, Alberto ^{[3
,4
]}

Farina, Andrea ^{[4
]}

D'Andrea, Cosimo ^{[3
,5
]}

Tajahuerce, Enrique ^{[1
]}

机构：

[1] Univ Jaume 1, Inst New Imaging Technol INIT, GROC UJI, Avda Sos Baynat S-N, Castellon de La Plana 12071, Spain

[2] ENS Univ PSL, Sorbonne Univ, Lab Kastler Brossel, CNRS,Coll France, 24 Rue Lhomond, F-75005 Paris, France

[3] Politecn Milan, Dipartimento Fis, Piazza L da Vinci 32, I-20133 Milan, Italy

[4] CNR, Ist Foton & Nanotecnol, Piazza L da Vinci 32, I-20133 Milan, Italy

[5] Ist Italiano Tecnol, Ctr Nano Sci & Technol, Via Pascoli 70-3, I-20133 Milan, Italy

来源：

UNCONVENTIONAL OPTICAL IMAGING III | 2022年 / 12136卷

关键词：

Computational imaging; single-pixel imaging; data fusion; multidimensional imaging; multispectral imaging; fluorescence life-time imaging;

D O I：

10.1117/12.2621587

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

We present a technique for multispectral fluorescence lifetime imaging with high spatial resolution by combining both single-pixel and data fusion imaging techniques. The system relies on the combined use of three different sensors: two SP cameras capturing multispectral and time-resolved information, and a conventional 2D array detector capturing high spatial resolution images The resultant giga-voxel 4D hypercube is acquired in a fast manner measuring only 0.03% of the dataset. The fusion procedure is done by solving a regularization problem which is efficiently solved via gradient descent. The system can be used to identify fluorophore species.

引用

页数：4

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