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

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

6.9K
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...
6.9K

You might also read

Related Articles

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

Sort by
Same author

CRISPR/Cas9-Mediated Knockout of <i>BmGDAP2</i> in the Silkworm, <i>Bombyx mori</i>: Extended Lifespan and Altered Gene Expression Impacting Developmental Pathways.

Insects·2025
Same author

Mechanism of a Trapezoidal Magnetic Field Enhanced Helium Plasma Jet for Improving the Surface Modification Effect on Polyimide Films.

Langmuir : the ACS journal of surfaces and colloids·2025
Same author

SGDAcn is a suppressor for silk gland endoreplication and development.

Insect science·2025
Same author

The Ability to Digest Cellulose Can Significantly Improve the Growth and Development of Silkworms.

Insects·2025
Same author

Relationships between students' perceived campus walkability, mental health, and life satisfaction during COVID-19.

Scientific reports·2024
Same author

Silkworm Hemolymph and Cocoon Metabolomics Reveals Valine Improves Feed Efficiency of Silkworm Artificial Diet.

Insects·2024

Related Experiment Video

Updated: Jun 14, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.4K

Real-world video superresolution enhancement method based on the adaptive down-sampling model.

Xu Zhang1, Jinxin Wu2

  • 1Software Engineering Institute, Xiamen University of Technology, Xiamen, 361000, China. zx9886518@163.com.

Scientific Reports
|September 4, 2024
PubMed
Summary

Superresolution technology enhances image and video resolution for 5G networks. Combining deep learning with traditional methods like block-matching-3D (BM3D) and adaptive downsampling models (ADM) improves visual quality and transmission efficiency.

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

379
High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

Related Experiment Videos

Last Updated: Jun 14, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.4K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

379
High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

Area of Science:

  • Computer Vision
  • Deep Learning
  • Image Processing

Background:

  • Increasing demand for high-resolution images and videos due to 5G technology.
  • Growing server transmission pressure necessitates efficient image/video resolution enhancement.
  • Shift from traditional algorithms to deep learning for superior visual display.

Purpose of the Study:

  • To enhance image and video resolution using advanced superresolution techniques.
  • To improve the authenticity and subjective viewing experience of recovered images.
  • To optimize superresolution algorithm performance for specific camera styles.

Main Methods:

  • Integration of the traditional block-matching-3D (BM3D) algorithm as a postprocessing module.
  • Utilization of the adaptive-downsampling model (ADM) for training camera-specific models.
  • Downsampling high-resolution (HR) data sequences to create low-resolution (LR) training sets.

Main Results:

  • BM3D postprocessing mitigates GAN network recovery artifacts, enhancing image authenticity.
  • ADM enables tailored superresolution models, improving results for specific camera styles.
  • The proposed method achieves performance improvements of 0.1–0.3 dB.

Conclusions:

  • Deep learning-based superresolution, enhanced by BM3D and ADM, offers superior image quality.
  • The adaptive downsampling approach improves superresolution performance and visual authenticity.
  • This research addresses the growing demand for high-resolution content in the 5G era.