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...

Downsampling

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...

You might also read

Related Articles

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

Sort by

Same author

Isobavachalcone induces concurrent apoptosis and pyroptosis in anaplastic thyroid cancer cells by modulating the caspase-mediated cleavage of PARP and GSDME.

American journal of cancer research·2026

Same author

Robust Incipient Fault Diagnosis of Rolling Element Bearings Under Small-Sample Conditions Using Refined Multiscale Rating Entropy.

Entropy (Basel, Switzerland)·2026

Same author

Predictive factors and a nomogram for hemodynamic instability during operation in patients with pheochromocytomas and paragangliomas.

Surgical endoscopy·2025

Same author

Optimizing the angle of arrival positioning error of a UAV via an improved nutcracker optimization algorithm.

Scientific reports·2025

Same author

Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning.

Sensors (Basel, Switzerland)·2025

Same author

Comparative analysis of dehazing algorithms on real-world hazy images.

Scientific reports·2025

Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026

Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026

Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026

Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026

Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026

Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 21, 2025

Test Samples for Optimizing STORM Super-Resolution Microscopy

Test Samples for Optimizing STORM Super-Resolution Microscopy

Published on: September 6, 2013

Single image de-raining by multi-scale Fourier Transform network.

Chaobing Zheng¹, Yao Yao², Wenjian Ying³

¹Institute of Robotics and Intelligent Systems, School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China.

|March 18, 2025

Summary

This summary is machine-generated.

This study introduces a new single-image de-raining method using Fourier Transform prior knowledge. It efficiently removes rain streaks and enhances image clarity, outperforming current methods.

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations

Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations

Published on: March 19, 2021

Related Experiment Videos

Last Updated: May 21, 2025

Test Samples for Optimizing STORM Super-Resolution Microscopy

Test Samples for Optimizing STORM Super-Resolution Microscopy

Published on: September 6, 2013

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations

Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations

Published on: March 19, 2021

Area of Science:

Computer Vision
Image Processing
Artificial Intelligence

Background:

Single-image de-raining is challenging due to streak variability.
Data-driven methods often require large datasets and lack interpretability.

Purpose of the Study:

To propose a novel, interpretable, and efficient single-image de-raining method.
To leverage Fourier Transform prior knowledge for improved rain streak removal.

Main Methods:

Decomposing rainy images into amplitude and phase components using Fourier Transform.
Applying data-driven algorithms to process amplitude and phase components separately.
Reconstructing enhanced features and refining with a multi-scale neural network with attention mechanisms.

Main Results:

The proposed method significantly outperforms state-of-the-art de-raining approaches.
Achieved superior qualitative and quantitative evaluations in experimental results.
Demonstrated improved image clarity and robustness in de-raining.

Conclusions:

The novel approach effectively combines Fourier Transform and data-driven techniques.
Offers a more interpretable and efficient solution for single-image de-raining.
Represents a significant advancement in image restoration research.