Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

1.9K
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...
1.9K
IR Absorption Frequency: Hybridization01:21

IR Absorption Frequency: Hybridization

712
Hydrocarbons such as alkanes, alkenes, and alkynes show characteristic C–H stretching absorption bands. These IR stretching frequencies depend on the hybridization of the involved carbon atom and can be explained in terms of the s character of each hybridized atomic orbital.
Among the sp, sp2, and sp3 hybridized orbitals, sp orbitals have the maximum s character (50%). Consequently, the electrons are held more closely to the nucleus, resulting in stronger and shorter C–H bonds that...
712
IR Spectrometers01:25

IR Spectrometers

1.2K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
1.2K
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

940
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...
940
Flame Photometry: Overview01:02

Flame Photometry: Overview

667
Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
667
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

1.0K
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...
1.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A Semi-Supervised Object Detector Based on Adaptive Weighted Active Learning and Orthogonal Data Augmentation.

Sensors (Basel, Switzerland)·2025
Same author

SP-IGAN: An Improved GAN Framework for Effective Utilization of Semantic Priors in Real-World Image Super-Resolution.

Entropy (Basel, Switzerland)·2025
Same author

Single-Character-Based Embedding Feature Aggregation Using Cross-Attention for Scene Text Super-Resolution.

Sensors (Basel, Switzerland)·2025
Same author

Activation extending based on long-range dependencies for weakly supervised semantic segmentation.

PloS one·2023
Same author

FECFusion: Infrared and visible image fusion network based on fast edge convolution.

Mathematical biosciences and engineering : MBE·2023
Same author

Does the medical insurance system play a real role in reducing catastrophic economic burden in elderly patients with cardiovascular disease in China? Implication for accurately targeting vulnerable characteristics.

Globalization and health·2021

相关实验视频

Updated: Jul 21, 2025

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K

SCFusion:基于突出的补偿的红外和可见融合.

Haipeng Liu1, Meiyan Ma1, Meng Wang1,2

  • 1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.

Entropy (Basel, Switzerland)
|July 29, 2023
PubMed
概括

这项研究引入了一种基于突出补偿的新型图像融合方法,用于在低光条件下增强红外和可见图像. 该技术改善了目标特征描述和全球场景感知,优于现有的融合算法.

关键词:
深度学习是一种深度学习.图像融合 图像融合 图像融合红外和可见图像中的红外和可见图像.显著的补偿显著的补偿

更多相关视频

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

571
Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy
07:53

Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy

Published on: August 5, 2022

2.1K

相关实验视频

Last Updated: Jul 21, 2025

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K
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

571
Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy
07:53

Group Synchronization During Collaborative Drawing Using Functional Near-Infrared Spectroscopy

Published on: August 5, 2022

2.1K

科学领域:

  • 计算机视觉 计算机视觉
  • 图像处理 图像处理
  • 人工智能的人工智能

背景情况:

  • 目前的深度学习融合方法与低光红外图像作斗争,导致细节和对比度差.
  • 现有的算法往往无法充分利用红外和可见模式的互补信息.

研究的目的:

  • 通过有效地整合红外和可见图像特征,开发用于低光条件的优质图像融合方法.
  • 为了解决当前融合技术在纹理细节,目标对比度和视觉感知方面的局限性.

主要方法:

  • 提出了一种基于突出补偿的融合方法,使用多尺度边缘梯度模块 (MEGB) 来提取纹理.
  • 引入了一个突出密度残余模块 (SRDB) 用于突出地图生成和特征提取,以突出损失进行训练.
  • 实现空间偏差模块 (SBM) 以有效地融合全球和本地图像信息.

主要成果:

  • 广泛的实验表明,与现有方法相比,在描述目标特征和全球场景方面具有显著的优势.
  • 废弃性研究证实了拟议模块 (MEGB,SRDB,SBM) 的有效性.
  • 该方法显示了高级视觉任务的便利性,特别是语义细分.

结论:

  • 提出的基于突出补偿的融合方法在低光场景中显著提高了图像质量.
  • 新型模块有效地提取和融合多模式图像信息,改善特征表示.
  • 这种方法为红外和可见图像融合提供了强大的解决方案,并有利于下游视觉任务.