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Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...

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Updated: Nov 21, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Super-resolution time-resolved imaging using computational sensor fusion.

C Callenberg¹, A Lyons², D den Brok¹

¹Institute of Computer Science, University of Bonn, Bonn, Germany.

Scientific Reports

|January 19, 2021

Summary

This summary is machine-generated.

This study introduces a novel sensor fusion technique combining single-photon-avalanche-diode (SPAD) and CMOS camera data. This method significantly enhances spatial resolution in time-resolved imaging for applications like LIDAR and fluorescence lifetime imaging (FLIM).

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Area of Science:

Optics and Imaging
Biomedical Engineering
Photonics

Background:

High-precision 3D imaging is crucial for LIDAR and FLIM but often requires sacrificing spatial for temporal resolution.
Acquiring full 3D data cubes rapidly presents significant challenges, necessitating innovative imaging solutions.

Purpose of the Study:

To develop a sensor fusion method that overcomes the spatial-temporal resolution trade-off in imaging.
To enhance the spatial resolution of time-resolved imaging techniques using complementary sensor data.

Main Methods:

A sensor fusion approach combining low-spatial/high-temporal resolution SPAD data with high-spatial/no-temporal resolution CMOS data.
Image blurring on the SPAD array followed by computational sensor fusion to reconstruct enhanced images.

Main Results:

Reconstruction of time-resolved images with significantly improved spatial resolution compared to SPAD input.
Demonstrated numerical upsampling by a factor of [Formula: see text] and experimental upsampling up to [Formula: see text].
Successful application of the technique in LIDAR and fluorescence lifetime imaging (FLIM) of cancer cells.

Conclusions:

The developed sensor fusion technique effectively enhances spatial resolution in time-resolved imaging.
This method enables high spatial resolution SPAD imaging and accelerates FLIM imaging by over an order of magnitude.
Paves the way for advanced imaging capabilities in LIDAR and microscopy.