Super-resolution time-resolved imaging using computational sensor fusion

Clara Callenberg, Ashley Lyons*, D. den Brok, Areeba Fatima, A. Turpin, Vytas Zickus, Laura Machesky, Jamie Whitelaw, Daniele Faccio*, M. B. Hullin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
4 Downloads (Pure)


Imaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fuorescence lifetime imaging. However, compromises that sacrifce, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube isrequired in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard
CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at signifcantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor 12 × 12, and demonstrating up to 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of
fuorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.
Original languageEnglish
Article number1689
Number of pages8
JournalScientific Reports
Publication statusPublished - 18 Jan 2021
Externally publishedYes


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