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 Videos

Adaptive autofocusing: a closed-loop perspective.

Ying Zhang1, Changyun Wen, Yeng Chai Soh

  • 1Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075. yzhang@simtech.a-star.edu.sg

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|April 21, 2005
PubMed
Summary
This summary is machine-generated.

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

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same author

Diffusion Graph Transformer for Learning Controllability Robustness in Large-Scale Networks.

IEEE transactions on cybernetics·2026
Same author

Accelerated Reinforcement Learning With Verifiable Excitation for Cubic Convergence.

IEEE transactions on neural networks and learning systems·2026
Same author

Adaptive Hierarchical Event-Triggered H<sub>∞</sub> Output Tracking of IT2 Fuzzy Heterogeneous Multiagent Systems Under Multiple-Channel DoS Attacks.

IEEE transactions on cybernetics·2026
Same author

Distributed FilterNet Reinforcement Learning for Achieving Output Consensus in Heterogeneous Multiplayer Multiagent Systems.

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

Peaking Removing in Semi-Global Stabilization for a Class of Nonlinear Cascaded Systems Based on Control Barrier Functions.

IEEE transactions on cybernetics·2025
Same journal

Multi-module collaborative optimization-driven fast speckle correlation imaging in variable environments.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Secrecy performance analysis of NOMA-UWOC systems over a vertically stratified WGG oceanic turbulence channel.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Backscattering of plane waves in a composite system containing a rough surface and anisotropic scatterers.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Aspherical surface construction methods based on extended Jacobi polynomials.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

OCT sidelobe suppression method based on dual-path phase sinusoidal modulation and minimum value fusion.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Optical design concepts using wavelength-selective diffractive optics to enable miniaturized multimodal endoscopic imaging across separated spectral ranges.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
See all related articles

This study introduces an adaptive autofocusing method that updates focus measures using image moments. This approach ensures high accuracy by reducing reliance on image content and suppressing noise and time delays.

Area of Science:

  • Optics and Image Processing
  • Computer Vision

Background:

  • Autofocusing systems often depend heavily on image content, leading to inaccuracies.
  • Noise and processing time delays can degrade the performance of traditional autofocusing methods.

Purpose of the Study:

  • To develop an adaptive autofocusing scheme that overcomes limitations of content-dependent methods.
  • To enhance autofocusing accuracy by mitigating noise and time delay effects.

Main Methods:

  • Constructing a focus measure using image moments.
  • Developing an adaptive focus-tuning strategy for closed-loop estimation.
  • Implementing adaptive updating of the focus measure.

Main Results:

  • The proposed scheme demonstrates reduced dependence on image content.

Related Experiment Videos

  • Effective suppression of noise and time delay effects in optical imaging.
  • High accuracy in autofocusing achieved through adaptive closed-loop operation.

    • Conclusions:

    • The adaptive autofocusing scheme offers robust and accurate focusing.
    • The method is validated through both simulations and experimental results.
    • This approach advances autofocusing technology for optical imaging applications.