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 Experiment Video

Updated: Sep 11, 2025

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

635

Single-pixel imaging via data-driven and deep image prior dual networks.

Jing-Yi Shi, Jia-Qi Song, Peng-Cheng Ji

    Optics Express
    |August 13, 2025
    PubMed
    Summary

    A new dual-network framework improves single-pixel imaging (SPI) by combining deep image prior networks (DIP-Net) and data-driven networks (DD-Net). This approach reconstructs high-quality images faster and more effectively, even with limited data.

    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

    Single-shot lensless dual-mode ultraviolet imaging based on diffuser speckle modulation.

    Optics letters·2026
    Same author

    Lignin-tailored synergistic catalyst with cobalt single-atom and zinc clusters dual-site for conversion of hemicellulose to lactic acid.

    Bioresource technology·2026
    Same author

    [Detoxification Effect of Selenium Application on Pak Choi in Arsenic-contaminated Soil and Its Mechanism].

    Huan jing ke xue= Huanjing kexue·2026
    Same author

    Utilizing Multimodal Logic Fusion to Identify the Types of Food Waste Sources.

    Sensors (Basel, Switzerland)·2026
    Same author

    Yttrium-90 downstages giant hepatocellular carcinoma to resectable size.

    Hepatobiliary & pancreatic diseases international : HBPD INT·2026
    Same author

    Tabletop pulsed x-ray ghost imaging with a single-pixel detector.

    The Review of scientific instruments·2025

    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • Machine Learning for Imaging

    Background:

    • Single-pixel imaging (SPI) reconstructs images using a single-pixel detector, often relying on deep neural networks.
    • Deep image prior networks (DIP-Net) offer quality but require many iterations; data-driven networks (DD-Net) are fast but need similar training data.
    • Sub-sampling conditions in SPI reduce effective information, challenging image reconstruction quality.

    Purpose of the Study:

    • To introduce a novel dual-network iterative optimization (SPI-DNIO) framework for enhanced single-pixel imaging.
    • To overcome the limitations of existing DIP-Net and DD-Net approaches in SPI.
    • To improve image reconstruction quality and reduce iteration count in SPI, especially at low sampling rates.

    Main Methods:

    More Related Videos

    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.3K
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    17.8K

    Related Experiment Videos

    Last Updated: Sep 11, 2025

    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

    635
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.3K
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    17.8K
    • Developed a dual-network iterative optimization (SPI-DNIO) framework integrating DD-Net and DIP-Net strengths.
    • Designed a residual block with gradient information to enhance deep network learning from low-sampling-rate SPI data.
    • Conducted indoor active lighting and outdoor passive lighting experiments to validate the framework.

    Main Results:

    • The SPI-DNIO framework achieved high-quality image reconstruction with significantly fewer iterations compared to traditional methods.
    • The gradient-enriched residual block improved the network's ability to learn from SPI inputs with less information.
    • Experimental results demonstrated exceptional reconstruction capabilities and strong generalization performance across different lighting conditions.

    Conclusions:

    • The proposed SPI-DNIO framework effectively combines the advantages of DD-Net and DIP-Net for superior SPI performance.
    • The enhanced residual block design addresses the challenge of limited information in low sampling rate SPI.
    • The framework shows promising results for both active and passive lighting scenarios, highlighting its versatility and effectiveness.