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

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

1.2K
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
1.2K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

2.5K
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...
2.5K
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

1.1K
In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
1.1K
IR Spectrum01:19

IR Spectrum

1.3K
When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0%...
1.3K
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

7.2K
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...
7.2K
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

601
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...
601

You might also read

Related Articles

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

Sort by
Same author

Proximity-Driven Protein Ligation Beyond the Concentration Limit.

Journal of the American Chemical Society·2026
Same author

CMSV: Long-Read-Based Structural Variation Detection Through a CNN-Mamba Model.

Genes·2026
Same author

Proactive Health: A Culture-Centered Study on the Differential Health Practices of Older Adults in Elderly Care Institutions in China.

Health communication·2026
Same author

Direct Photoredox Synthesis of <i>N</i>-Linked Glycoproteins.

Journal of the American Chemical Society·2026
Same author

Elemental phosphorus-stabilized Ni<sub>2</sub>P for efficient electrooxidation of 5-hydroxymethylfurfural to 2,5-furandicarboxylic acid.

Chemical communications (Cambridge, England)·2026
Same author

Evaluation of a novel C2 pedicle screw insertion technique: a retrospective comparative clinical study and finite element analysis.

Scientific reports·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 22, 2025

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.2K

Infrared Small Target Detection Using Regional Feature Difference of Patch Image.

Guofeng Zhang1,2, Hongbing Ma1,3, Askar Hamdulla1

  • 1School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.

Sensors (Basel, Switzerland)
|May 20, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Gaussian fusion algorithm for enhanced small target detection in infrared imagery. The method effectively suppresses background clutter and improves target visibility, outperforming existing algorithms.

Keywords:
Gaussian fusion algorithmRegional Brightness Level MeasurementRegional Energy Cosinepatch imageregional patchstructure difference

More Related Videos

High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
11:05

High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Published on: January 21, 2015

33.4K
Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.9K

Related Experiment Videos

Last Updated: Sep 22, 2025

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.2K
High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
11:05

High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Published on: January 21, 2015

33.4K
Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.9K

Area of Science:

  • Computer Vision
  • Signal Processing
  • Infrared Imaging

Background:

  • Conventional small target detection algorithms struggle with background clutter.
  • Existing methods lack robustness and sensitivity in complex scenes.

Purpose of the Study:

  • To develop a robust algorithm for small target detection in infrared imagery.
  • To overcome limitations of local contrast methods in handling background clutter.

Main Methods:

  • Proposed a Gaussian fusion algorithm integrating multi-scale regional patch structure difference and Regional Brightness Level Measurement (RBLM).
  • Introduced Regional Energy Cosine (REC) to measure structural discrepancy.
  • Utilized RBLM for brightness difference characteristics.
  • Employed a self-adapting separation algorithm for target isolation.

Main Results:

  • The proposed algorithm effectively restrains background interference.
  • Demonstrated remarkable performance in strengthening target regions.
  • Outperformed current algorithms in both qualitative and quantitative evaluations.

Conclusions:

  • The novel Gaussian fusion algorithm significantly enhances small target detection.
  • The method offers superior robustness against background clutter in infrared images.