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

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

A Causal Lens on Non-RGB Vision Sensor Understanding in Vision-Language Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Advancing Causal Intervention in Image Captioning With Causal Prompt.

IEEE transactions on neural networks and learning systems·2025
Same author

Prompt Tuning of Deep Neural Networks for Speaker-Adaptive Visual Speech Recognition.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Enabling Visual Object Detection With Object Sounds via Visual Modality Recalling Memory.

IEEE transactions on neural networks and learning systems·2023
Same author

Deep learning-based classification system of bacterial keratitis and fungal keratitis using anterior segment images.

Frontiers in medicine·2023

Related Experiment Video

Updated: Feb 17, 2026

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
09:04

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display

Published on: January 14, 2020

10.3K

Ultrafast layer based computer-generated hologram calculation with sparse template holographic fringe pattern for 3-D

Hak Gu Kim, Yong Man Ro

    Optics Express
    |December 10, 2017
    PubMed
    Summary

    We developed a fast method for calculating computer-generated holograms (CGH) by leveraging sparse holographic fringe patterns. This approach significantly reduces computation time for 3D object displays.

    More Related Videos

    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

    16.1K
    Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization
    10:28

    Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

    Published on: July 5, 2016

    10.8K

    Related Experiment Videos

    Last Updated: Feb 17, 2026

    Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
    09:04

    Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display

    Published on: January 14, 2020

    10.3K
    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

    16.1K
    Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization
    10:28

    Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

    Published on: July 5, 2016

    10.8K

    Area of Science:

    • Optics and Photonics
    • Computer Graphics
    • Computational Imaging

    Background:

    • Computer-generated holography (CGH) is crucial for 3D display technologies.
    • Calculating CGH, especially for complex 3D objects, is computationally intensive.
    • Existing methods struggle with real-time performance requirements.

    Purpose of the Study:

    • To propose a novel, ultrafast layer-based CGH calculation method.
    • To exploit the inherent sparsity of hologram fringe patterns in 3D object layers.
    • To reduce the computational load for generating high-resolution holograms.

    Main Methods:

    • Devised a sparse template holographic fringe pattern.
    • Calculated holographic fringe patterns on a depth layer by summing sparse templates at object point positions.
    • Exploited the reduced size of sparse templates compared to the full CGH plane.

    Main Results:

    • Achieved CGH calculation times of 10-20 milliseconds for 1024x1024 pixel holograms.
    • Demonstrated visually plausible holographic results.
    • Significantly reduced computational load due to smaller sparse template sizes.

    Conclusions:

    • The proposed layer-based CGH calculation method offers significant speed improvements.
    • Exploiting fringe pattern sparsity is an effective strategy for fast CGH generation.
    • The method is suitable for real-time 3D holographic display applications.