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

Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Bandpass Sampling01:17

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...

You might also read

Related Articles

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

Sort by
Same author

Self-filtering monolithic organic/PbS quantum dot photodetector for visible and short-wave infrared selective vision in low-light.

Nature communications·2026
Same author

A Universal Approach to Enhancing Silicon Hot-Carrier Photodetectors for CMOS-Compatible SWIR Imaging.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Molecular and clinical disparity of <i>EGFR</i>-mutant non-small cell lung cancer (NSCLC) based on histopathological stage and <i>EGFR</i> molecular subtypes.

Translational lung cancer research·2026
Same author

Seeing through fibers: unsupervised image reconstruction in fiber bundle imaging systems.

Optics express·2026
Same author

Neural phase microscopy with metasurface optics for real-time and nanoscale quantitative phase imaging.

Nature communications·2026
Same author

Development of advanced sequential ray tracing simulator for lens systems using multi-functional holographic optical elements.

Optics express·2025
Same journal

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor.

Optics express·2026
Same journal

Robust 3D topography measurement of large-range high-aspect-ratio structures based on dual-domain statistical filtering in SD-OCT.

Optics express·2026
Same journal

Broadband transmissive terahertz metasurface for simultaneous quad-mode OAM multiplexing.

Optics express·2026
Same journal

Leveraging two-dimensional materials for high-sensitivity optical sensors: quasi-bound states in the continuum within hybrid metasurfaces.

Optics express·2026
Same journal

Resolution investigation for dual-spherical-wave optical scanning holographic microscopy: methods and performance.

Optics express·2026
Same journal

Robustness of parallel subnetwork-filtered diffractive deep neural networks.

Optics express·2026
See all related articles

Related Experiment Video

Updated: May 22, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Enhancing angular sampling rate of integral floating display using dynamically variable apertures.

Jisoo Hong1, Jiwoon Yeom, Byoungho Lee

  • 1School of Electrical Engineering, Seoul National University, Gwanak-Gu Gwanakro 1, Seoul 151-744, South Korea.

Optics Express
|April 27, 2012
PubMed
Summary
This summary is machine-generated.

Two novel methods improve integral floating display angular sampling rates using time-multiplexed variable apertures. This enhances expressible longitudinal range without compromising visual quality, with one method offering 2D/3D convertibility.

More Related Videos

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
05:57

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

Related Experiment Videos

Last Updated: May 22, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
05:57

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

Area of Science:

  • Optics and Photonics
  • Display Technology
  • Computer Vision

Background:

  • Integral imaging provides 3D display capabilities but is limited by angular sampling rate.
  • Low angular sampling restricts the expressible longitudinal range and depth perception.
  • Existing methods often involve trade-offs with other visual quality factors.

Purpose of the Study:

  • To propose novel methods for enhancing the angular sampling rate of integral floating displays.
  • To improve the expressible longitudinal range without sacrificing visual quality.
  • To introduce a 2D/3D convertible feature for integral floating display systems.

Main Methods:

  • Implementing dynamically variable apertures synchronized with elemental images.
  • Utilizing a time-multiplexing method to subdivide angular sampling steps.
  • Applying apertures in front of the lenslet array or directly on the floating lens.

Main Results:

  • Successfully enhanced the angular sampling rate of the integral floating display.
  • Demonstrated improvement in expressible longitudinal range.
  • Achieved enhanced angular sampling without compromising visual quality factors.
  • Developed a method enabling 2D/3D convertibility for the display system.

Conclusions:

  • The proposed dynamically variable aperture methods effectively enhance angular sampling rates in integral floating displays.
  • These techniques expand the expressible longitudinal range and offer 2D/3D display capabilities.
  • The methods provide a viable solution for improving integral imaging display performance without visual trade-offs.