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

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

You might also read

Related Articles

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

Sort by
Same author

Quantitative phosphoproteomics profiling reveals the regulatory mechanisms underlying high light stress in maize and rice.

Photosynthesis research·2026
Same author

Mesh-represented and learning-empowered hologram synthesis for full 3D holographic displays.

Nature communications·2026
Same author

Preclinical evaluation of the newly developed carina platform in robotic-assisted proctectomy with porcine and cadaveric models.

Scientific reports·2026
Same author

Depth-dependent phosphorus leaching risks in littoral soils of Lake Dianchi under extreme rainfall.

Environmental geochemistry and health·2026
Same author

Harnessing natural variation for photosynthetic improvement in next-generation crop breeding.

Journal of integrative plant biology·2026
Same author

Cytokinin histidine kinase receptors regulate multiple aspects of rice growth and development.

Plant physiology·2026

Related Experiment Video

Updated: May 21, 2026

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Towards Edge Holography via Implicit Neural Representation and Compression.

Hyunmin Ban, Wenbin Zhou, Yifan Peng

    IEEE Transactions on Visualization and Computer Graphics
    |May 19, 2026
    PubMed
    Summary
    This summary is machine-generated.

    We developed a new method for generating and compressing holographic images using implicit neural representations (INRs). This approach significantly reduces computational load and improves compression rates for realistic 3D holographic displays.

    More Related Videos

    Evaluation and Manipulation of Neural Activity Using Two-Photon Holographic Microscopy
    10:09

    Evaluation and Manipulation of Neural Activity Using Two-Photon Holographic Microscopy

    Published on: September 16, 2022

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
    05:45

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging

    Published on: March 31, 2022

    Related Experiment Videos

    Last Updated: May 21, 2026

    Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
    10:16

    Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

    Published on: February 8, 2014

    Evaluation and Manipulation of Neural Activity Using Two-Photon Holographic Microscopy
    10:09

    Evaluation and Manipulation of Neural Activity Using Two-Photon Holographic Microscopy

    Published on: September 16, 2022

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
    05:45

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging

    Published on: March 31, 2022

    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Machine Learning

    Background:

    • Holographic displays promise realistic 3D visualization for augmented and virtual reality.
    • Existing computer-generated holography (CGH) methods face challenges with high computational costs and limited realism.
    • Efficiently encoding hologram data for cloud-edge computing is difficult due to its high-frequency information.

    Purpose of the Study:

    • To present a display-aware, lightweight CGH framework for generating and compressing high-fidelity phase-only holograms.
    • To address the limitations of existing CGH methods in terms of computational burden and display realism.
    • To enable real-time streaming of holograms for wearable solutions.

    Main Methods:

    • Leveraged implicit neural representations (INRs) to treat hologram generation as a continuous function approximation problem.
    • Employed camera-calibrated wave propagation for accurate hologram synthesis.
    • Incorporated quantization-aware training and entropy coding for efficient deployment and compression.

    Main Results:

    • The proposed INR-CGH framework achieved image quality comparable to optimization-based methods for both 2D and 3D holograms.
    • Achieved up to an 11x compression rate with minimal quality loss using the compact INR representation.
    • Demonstrated decoding speeds of ≥250 fps, enabling edge holography.

    Conclusions:

    • The INR-CGH framework offers a computationally efficient and lightweight solution for high-fidelity hologram generation and compression.
    • The approach significantly improves compression rates and decoding speeds, paving the way for practical edge holography applications.
    • This method enhances the feasibility of realistic 3D visualization in wearable virtual and augmented reality solutions.