Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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 developed.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Discovery of an Orally Available Potent ER Aminopeptidase 1 (ERAP1) Inhibitor That Enhances Antitumor Responses and Limits Inflammatory Autoimmunity <i>In Vivo</i>.

Journal of medicinal chemistry·2026

Same author

Primitive neuronal component is a frequent finding among IDH-mutant astrocytomas with RB1 alterations.

Acta neuropathologica·2026

Same author

Rapid Genome Sequencing Shows Diagnostic Utility in Infants With Congenital Heart Defects.

Circulation. Genomic and precision medicine·2026

Same author

A graphene-coated AFM probe for durable and reproducible nanoscale electronic measurements.

Nanoscale advances·2026

Same author

Imaging in the fast lane: Challenges and opportunities for expanding access to MRI.

AJNR. American journal of neuroradiology·2026

Same author

Highly Accelerated 3D MRI of Brain Tumors Using Deep Modular Reconstruction Networks.

NMR in biomedicine·2026

Same journal

Peripheral B-cell receptor repertoire predicts immune-related adverse events following immune checkpoint inhibitor therapy in advanced renal cell carcinoma.

Scientific reports·2026

Same journal

Effects of black soldier fly (Hermetia illucens L.) larvae zoocompost on the mineral element content of blue honeysuckle berries.

Scientific reports·2026

Same journal

Investigation on absorption refrigeration performance of R1243zf with imidazolium ionic liquid as the working pairs.

Scientific reports·2026

Same journal

DeepTriage-CN: integrating clinical text with vital signs for emergency department admission prediction in an aging population.

Scientific reports·2026

Same journal

Gold nanoparticles as dual-action antiviral agents: disruption of SARS-CoV-2 viral envelopes and RNA integrity.

Scientific reports·2026

Same journal

Comparison of capillary microsampling and venous blood for multi-pathogen serosurveillance.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 8, 2026

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Published on: December 9, 2013

Exploiting colour-channel decorrelation for smartphone-based fluorescence detection.

Jay Little¹, Ella Mann-Andrews¹, Elliott M Ball²

¹Lancaster University, Lancaster, UK.

Scientific Reports

|July 6, 2026

Summary

This summary is machine-generated.

This study introduces a smartphone fluorescence detection method using color channel decorrelation. It enables low-cost authentication and sensing by analyzing correlations in images, not just intensity.

More Related Videos

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Published on: April 11, 2013

Related Experiment Videos

Last Updated: Jul 8, 2026

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Published on: December 9, 2013

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Published on: April 11, 2013

Area of Science:

Optics and Photonics
Consumer Electronics
Analytical Chemistry

Background:

Developing low-cost fluorescence detection is crucial for widespread authentication and sensing.
Existing methods often require specialized equipment, limiting accessibility.

Purpose of the Study:

To present a novel smartphone-based fluorescence detection technique.
To demonstrate its efficacy using controlled illumination and image analysis.

Main Methods:

Utilized 16-bit smartphone images under varied LED illumination.
Calculated Pearson Correlation Coefficient (PCC) between RGB camera channels.
Analyzed PCC distributions for fluorescent and non-fluorescent samples.

Main Results:

Non-fluorescent samples showed high PCC (≈1), indicating linear light scaling.
Fluorescent samples exhibited broader PCC distributions due to Stokes shift.
Simple PCC thresholding effectively discriminated between fluorescent and non-fluorescent materials.

Conclusions:

Smartphone fluorescence detection is feasible by analyzing RGB channel correlation.
The RGB-PCC method offers a low-cost, hardware-efficient alternative for visible-light fluorescence detection.
Potential applications include authentication, materials analysis, and portable sensing.