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

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

1.6K
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
1.6K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

7.3K
When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
7.3K

You might also read

Related Articles

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

Sort by
Same author

Discovering Partial Differential Equations With Neural Cellular Automata.

Artificial life·2026
Same author

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Fast Adversarial Training With Adaptive Step Size.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2023
Same author

BIGPrior: Toward Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2022
Same author

Training Provably Robust Models by Polyhedral Envelope Regularization.

IEEE transactions on neural networks and learning systems·2021
Same author

Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2020

Related Experiment Video

Updated: Apr 4, 2026

Near-Infrared Temperature Measurement Technique for Water Surrounding an Induction-heated Small Magnetic Sphere
08:52

Near-Infrared Temperature Measurement Technique for Water Surrounding an Induction-heated Small Magnetic Sphere

Published on: April 30, 2018

8.8K

Automatic and Accurate Shadow Detection Using Near-Infrared Information.

Dominic Rüfenacht, Clément Fredembach, Sabine Süsstrunk

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |September 10, 2015
    PubMed
    Summary

    This study introduces a novel shadow detection method using near-infrared (NIR) imaging. The technique accurately identifies shadows by analyzing visible and NIR light, outperforming existing algorithms in speed and precision.

    More Related Videos

    Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS
    11:04

    Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS

    Published on: May 3, 2011

    15.2K
    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
    06:50

    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

    Published on: November 8, 2019

    7.1K

    Related Experiment Videos

    Last Updated: Apr 4, 2026

    Near-Infrared Temperature Measurement Technique for Water Surrounding an Induction-heated Small Magnetic Sphere
    08:52

    Near-Infrared Temperature Measurement Technique for Water Surrounding an Induction-heated Small Magnetic Sphere

    Published on: April 30, 2018

    8.8K
    Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS
    11:04

    Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS

    Published on: May 3, 2011

    15.2K
    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
    06:50

    O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

    Published on: November 8, 2019

    7.1K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Remote Sensing

    Background:

    • Traditional shadow detection methods struggle with dark objects.
    • Digital cameras exhibit unique sensitivity to the near-infrared (NIR) spectrum.

    Purpose of the Study:

    • To develop a fast and accurate automatic shadow detection algorithm.
    • To leverage NIR spectrum sensitivity for improved shadow identification.

    Main Methods:

    • Utilizing visible and NIR image data to create a shadow candidate map.
    • Refining the shadow map using visible-to-NIR image ratios.
    • Analyzing distinct light source spectra in the NIR band.

    Main Results:

    • The proposed method accurately detects shadows, even on dark objects.
    • Achieved superior accuracy and computational efficiency compared to state-of-the-art algorithms.
    • Validated on a diverse database of real-world shadow conditions.

    Conclusions:

    • The NIR-based shadow detection method offers significant improvements in accuracy and speed.
    • This approach effectively overcomes limitations of existing shadow detection techniques.
    • Demonstrated practical applicability across various illumination scenarios.