Time-resolved multispectral imaging has many applications in di erent fields, which range from characterization of biological tissues to environmental monitoring. In particular, optical techniques, such as lidar and fluorescence l ifetime i maging, r equire i maging a t the subnanosecond scales over an extended area. In this paper, we demonstrate experimentally a time-resolved multispectral acquisition scheme based on single-pixel imaging. Single-pixel imaging is an emerging paradigm that provides low-cost high-quality images. Here, we use an adaptive strategy that allows acquisition and image reconstruction times to be reduced drastically with respect to conventional single-pixel approaches that are based on compressed sensing or full basis scans. Adaptive time-resolved multispectral imaging scheme can have significant applications in biological imaging, at scales from macroscopic to microscopic.

Time-resolved multispectral imaging based on an adaptive single-pixel camera

Valentini Gianluca;Farina Andrea
2018

Abstract

Time-resolved multispectral imaging has many applications in di erent fields, which range from characterization of biological tissues to environmental monitoring. In particular, optical techniques, such as lidar and fluorescence l ifetime i maging, r equire i maging a t the subnanosecond scales over an extended area. In this paper, we demonstrate experimentally a time-resolved multispectral acquisition scheme based on single-pixel imaging. Single-pixel imaging is an emerging paradigm that provides low-cost high-quality images. Here, we use an adaptive strategy that allows acquisition and image reconstruction times to be reduced drastically with respect to conventional single-pixel approaches that are based on compressed sensing or full basis scans. Adaptive time-resolved multispectral imaging scheme can have significant applications in biological imaging, at scales from macroscopic to microscopic.
2018
Istituto di fotonica e nanotecnologie - IFN
wavelets
image-reconstruction
time-resolved imaging
adaptive imaging
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/348249
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