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

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

8.9K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
8.9K
Gradient and Del Operator01:14

Gradient and Del Operator

4.9K
In mathematics and physics, the gradient and del operator are fundamental concepts used to describe the behavior of functions and fields in space. The gradient is a mathematical operator that gives both the magnitude and direction of the maximum spatial rate of change. Consider a person standing on a mountain. The slope of the mountain at any given point is not defined unless it is quantified in a particular direction. For this reason, a "directional derivative" is defined, which is a vector...
4.9K

You might also read

Related Articles

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

Sort by
Same author

[ATM/H2AX and repair of sperm-DNA damage during cryopreservation].

Zhonghua nan ke xue = National journal of andrology·2011
Same author

Predicting accident frequency at their severity levels and its application in site ranking using a two-stage mixed multivariate model.

Accident; analysis and prevention·2011
Same author

Photothermally enhanced photodynamic therapy delivered by nano-graphene oxide.

ACS nano·2011
Same author

[Characteristics of soil respiration in Phyllostachys edulis forest in Wanmulin Natural Reserve and related affecting factors].

Ying yong sheng tai xue bao = The journal of applied ecology·2011
Same author

Quality changes in sea urchin (Strongylocentrotus nudus) during storage in artificial seawater saturated with oxygen, nitrogen and air.

Journal of the science of food and agriculture·2011
Same author

Global effect of an RNA polymerase β-subunit mutation on gene expression in the radiation-resistant bacterium Deinococcus radiodurans.

Science China. Life sciences·2011
Same journal

Denoising algorithm of Φ-OTDR systems based on adaptive fractional wavelet transform denoising.

Optics express·2026
Same journal

Millisecond photon-to-photon latency and high-speed volumetric projection system for optogenetics.

Optics express·2026
Same journal

Polarization-encoded coaxial structured light for high-precision 3D surface profilometry.

Optics express·2026
Same journal

Discrete freeform optical design based on collaborative optimization of point cloud and local normals.

Optics express·2026
Same journal

Ultrafast ghost imaging with 25 GHz speckle switching and wavelength-division multiplexing.

Optics express·2026
Same journal

Atomic vapor cells fabricated by femtosecond laser welding of standard-optical-quality glass.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.7K

Edge detection based on gradient ghost imaging.

Xue-Feng Liu, Xu-Ri Yao, Ruo-Ming Lan

    Optics Express
    |February 3, 2016
    PubMed
    Summary
    This summary is machine-generated.

    Gradient ghost imaging (GGI) enables direct edge detection without the original image. This method significantly enhances the signal-to-noise ratio for improved object edge identification.

    More Related Videos

    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

    12.7K
    Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging
    07:15

    Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

    Published on: July 11, 2025

    3.8K

    Related Experiment Videos

    Last Updated: Mar 26, 2026

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
    08:27

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

    Published on: January 5, 2024

    1.7K
    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

    12.7K
    Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging
    07:15

    Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

    Published on: July 11, 2025

    3.8K

    Area of Science:

    • Optical imaging
    • Computational imaging
    • Image processing

    Background:

    • Traditional edge detection methods often require the original image and can be sensitive to noise.
    • Ghost imaging (GI) offers a unique approach to image acquisition by correlating light patterns with detected intensities.

    Purpose of the Study:

    • To experimentally demonstrate edge detection using gradient ghost imaging (GGI) in the gradient domain.
    • To evaluate the performance enhancement of GGI compared to standard GI for edge detection.

    Main Methods:

    • Modification of a random light field to implement gradient ghost imaging (GGI).
    • Experimental setup using a double-slit for one- and two-dimensional edge detection.
    • Simulation-based study of GGI for gray-scale objects.

    Main Results:

    • GGI directly provides object edges without reconstructing the original image.
    • Significant improvement in signal-to-noise ratio (SNR) for edge detection using GGI.
    • Enhanced SNR observed in both one- and two-dimensional edge detection experiments.

    Conclusions:

    • Gradient ghost imaging (GGI) is an effective technique for direct edge detection.
    • GGI offers substantial SNR enhancement, particularly beneficial for sparse edges and high-transmittance objects.
    • The advantages of GGI position it as a valuable tool for real-world edge detection applications.