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...

Confocal Fluorescence Microscopy

Confocal Fluorescence Microscopy

Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...

You might also read

Related Articles

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

Sort by

Same author

Comparative assessment of endogenous, integrated, and exogenous biomethanation strategies: performance, microbial community and metabolic pathways.

Bioresource technology·2026

Same author

Empowering entity synonym set generation using flexible perceptual field and multi-layer contextual information.

PloS one·2025

Same author

High-speed spectral imaging via multispectral pulse illumination and temporal-spectral decoupling.

Optics letters·2025

Same author

Large-scale scattering-augmented optical encryption.

Nature communications·2024

Same author

SpectraTrack: megapixel, hundred-fps, and thousand-channel hyperspectral imaging.

Nature communications·2024

Same author

Towards large-scale single-shot millimeter-wave imaging for low-cost security inspection.

Nature communications·2024

Same journal

Gaussian-modulated continuous-variable quantum key distribution over 60 km fiber using an integrated silicon photonic receiver.

Optics letters·2026

Same journal

E2E-OCT: end-to-end joint learning model using optical coherence tomography images for vocal cord leukoplakia diagnosis.

Optics letters·2026

Same journal

Holographic generation of panoramic 3D scenes by concave ellipsoidal mirror reflection.

Optics letters·2026

Same journal

Dual-pilot phase recovery with pair-wise maximum-ratio combining for coherent PONs.

Optics letters·2026

Same journal

Mapping the whispering gallery modes of a CaF<sub>2</sub> disk resonator with half-tapered fibers to estimate the fundamental mode volume.

Optics letters·2026

Same journal

Quantitative estimation of deep-subwavelength scale via dark-field scattering axial energy concentration decay profiles.

Optics letters·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 9, 2025

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Sparse single-pixel imaging via optimization in nonuniform sampling sparsity.

Rong Yan, Daoyu Li, Xinrui Zhan

|December 1, 2023

Summary

This summary is machine-generated.

This study introduces a novel sparse sampling method for single-pixel imaging, enhancing reconstruction accuracy while reducing imaging time. A new sparsity metric aids in selecting optimal sampling forms for improved performance.

More Related Videos

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution

Published on: August 16, 2012

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

Related Experiment Videos

Last Updated: Jul 9, 2025

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution

Published on: August 16, 2012

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

Area of Science:

Optics and photonics
Computational imaging
Signal processing

Background:

Single-pixel imaging (SPI) faces challenges in reducing imaging time without compromising reconstruction accuracy.
Nonuniform sparse sampling is a cost-effective approach for SPI, but existing methods lack intuitive sparsity analysis.
This deficiency hinders understanding of adjustable ranges and optimal sampling form selection, impacting overall performance.

Purpose of the Study:

To develop a sparse sampling method for SPI with a wide adjustable range.
To define a sparsity metric for guiding the selection of sampling forms.
To address the limitations in current sparsity analysis for SPI.

Main Methods:

Implementation of a novel sparse sampling strategy for single-pixel imaging.
Definition and application of a quantitative sparsity metric.
Comprehensive analysis and discussion to identify optimal sampling forms.

Main Results:

A sparse sampling method with a wide adjustable range was successfully developed.
A sparsity metric was defined to guide the selection of sampling forms.
An optimal sampling form yielding satisfying reconstruction accuracy was identified.

Conclusions:

The developed method and sparsity metric address the lack of intuitive analysis in existing SPI sparse sampling techniques.
This work provides a framework for adjusting SPI methods to different situations and needs.
The findings contribute to improving the efficiency and accuracy of single-pixel imaging.