Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Pyrolytic hydrocarbon growth from cyclopentadiene.

The journal of physical chemistry. A·2010
Same author

In(III)-catalyzed tandem reaction of chromone-derived Morita-Baylis-Hillman alcohols with amines.

Organic & biomolecular chemistry·2010
Same author

Regression-based multi-trait QTL mapping using a structural equation model.

Statistical applications in genetics and molecular biology·2010
Same author

Elevated expression of APE1/Ref-1 and its regulation on IL-6 and IL-8 in bone marrow stromal cells of multiple myeloma.

Clinical lymphoma, myeloma & leukemia·2010
Same author

Accelerated aging of intervertebral discs in a mouse model of progeria.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society·2010
Same author

The synthesis of a multiblock osteotropic polyrotaxane by copper(I)-catalyzed huisgen 1,3-dipolar cycloaddition.

Macromolecular bioscience·2010

Related Experiment Video

Updated: Jun 10, 2025

Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations
13:13

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

Published on: March 19, 2021

2.8K

Event-Assisted Recurrent Network for Arbitrary-Temporal-Scale Blurry Image Unfolding.

Pengyu Zhang, Hao Ju, Weihua He

    IEEE Transactions on Neural Networks and Learning Systems
    |October 14, 2024
    PubMed
    Summary

    This study introduces a novel framework using event cameras to recover sharp image sequences from motion-blurred images at any temporal scale. This approach overcomes limitations of prior methods, enabling flexible recovery of latent frames.

    More Related Videos

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

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

    Published on: December 15, 2023

    478
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.7K

    Related Experiment Videos

    Last Updated: Jun 10, 2025

    Time-Lapse Imaging of Neuronal Arborization using Sparse Adeno-Associated Virus Labeling of Genetically Targeted Retinal Cell Populations
    13:13

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

    Published on: March 19, 2021

    2.8K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

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

    Published on: December 15, 2023

    478
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.7K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Biologically Inspired Computing

    Background:

    • Recovering sharp image sequences from motion blur is a significant challenge in computer vision.
    • Event cameras offer high temporal resolution, aiding motion blur reduction.
    • Existing methods lack flexibility in recovering sharp frames across arbitrary temporal scales.

    Purpose of the Study:

    • To propose an event-assisted framework for blurry image unfolding across arbitrary temporal scales.
    • To enable the recovery of a variable number of latent sharp frames from motion-blurred images.

    Main Methods:

    • Utilizing a bio-inspired event camera for high-temporal-resolution data acquisition.
    • Employing a bi-directional recurrent network to encode event data for each latent frame.
    • Fusing blurry image features with event features.
    • Implementing a bi-directional latent sequence decoder (BiLSD) for sharp frame generation.

    Main Results:

    • The proposed method achieves superior performance compared to state-of-the-art techniques for fixed-frame recovery.
    • Demonstrated effective generalization to blurry image unfolding across arbitrary temporal scales.
    • Successfully recovered sequences of latent sharp frames with high fidelity.

    Conclusions:

    • The developed framework effectively addresses the limitation of fixed temporal scales in previous methods.
    • Event camera data significantly enhances the recovery of sharp sequences from motion-blurred images.
    • The proposed approach offers a flexible and powerful solution for motion deblurring across diverse temporal scales.