Jove
Visualize
Contact Us

Related Concept Videos

Deconvolution01:20

Deconvolution

254
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
254
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

7.6K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
7.6K
Light Acquisition02:16

Light Acquisition

8.6K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.6K
Convolution Properties II01:17

Convolution Properties II

283
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
283
Convolution Properties I01:20

Convolution Properties I

239
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
239
Reducing Line Loss01:18

Reducing Line Loss

193
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
193

You might also read

Related Articles

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

Sort by
Same author

Molecular dynamics evidence for bidirectional feedback between PFAS and humic acid during composting: Interaction mechanisms, conformational reorganization, and diffusion regulation.

Journal of hazardous materials·2026
Same author

Association Between Stress Hyperglycemia Ratio and Death in Patients With Moderate to Severe Tricuspid Regurgitation.

Journal of the American Heart Association·2026
Same author

Early thermal pulses drive interfacial pre-aging and plastisphere pre-shaping: An overlooked pre-conditioning pathway in PLA microplastic aging during composting.

Journal of hazardous materials·2026
Same author

Clinical Application of the Modified Scleral Tunnel Intraocular Lens Ciliary Sulcus Suture-Fixation Technique.

Journal of ophthalmology·2026
Same author

Directional periodicity-aware factorized attention network for single-shot fringe projection profilometry.

Applied optics·2026
Same author

Molecular mechanism by which high temperature and RecBCD synergistically lower strand-separation barriers and promote destabilization of representative efflux-pump ARG fragments (macB/tetA) during hyperthermophilic composting.

Journal of hazardous materials·2026
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

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

15.7K

LFE-Net: a low-light fringe pattern enhancement method based on convolutional neural networks.

Linlin Wang, Wenke Xue, Qian Gao

    Applied Optics
    |August 12, 2025
    PubMed
    Summary

    This study introduces LFE-Net, a novel network for enhancing low-light fringe patterns in fringe projection profilometry (FPP). The method significantly improves image quality for 3D measurements, outperforming existing techniques.

    More Related Videos

    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
    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

    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

    15.7K
    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
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    17.8K

    Area of Science:

    • Optical Metrology
    • Computer Vision
    • Image Processing

    Background:

    • Fringe Projection Profilometry (FPP) is crucial for 3D measurements.
    • Low-light conditions degrade fringe pattern quality, hindering accuracy.
    • Existing enhancement methods struggle with low-light FPP images.

    Purpose of the Study:

    • To develop an effective deep learning network for enhancing low-light fringe patterns.
    • To improve the robustness and accuracy of FPP under adverse lighting.
    • To introduce a computationally efficient solution for low-light image enhancement.

    Main Methods:

    • Proposed LFE-Net architecture utilizing RGB and grayscale fringe patterns.
    • Incorporated Wavelet Transformation Preprocessing (WTP) for rich feature extraction.
    • Employed Residual Convolution Transformer Parallel (RCTP) for contextual information and flexibility.

    Main Results:

    • LFE-Net demonstrated superior performance in enhancing low-light fringe patterns compared to MSRCR, MIRNet, and HWMNet.
    • Achieved significantly faster computation times: 8.66% of MIRNet and 40.49% of HWMNet.
    • Experimental results validated the effectiveness and efficiency of the proposed network.

    Conclusions:

    • LFE-Net offers a robust solution for low-light fringe pattern enhancement in FPP.
    • The network provides high-quality results with improved computational efficiency.
    • This work advances the application of FPP in challenging lighting environments.