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Related Concept Videos

Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

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

IR Frequency Region: X–H Stretching

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 the 3500–3100 cm−1 range. Even though both O−H and N−H bonds vibrate at a similar...
IR Absorption Frequency: Hybridization01:21

IR Absorption Frequency: Hybridization

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 stretch at a...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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 C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
IR Spectrometers01:25

IR Spectrometers

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

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

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...

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Updated: Jul 4, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

Yiming Li, Bing Cao, Jiahe Feng

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |July 2, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces the Hyperbolic Cycle Alignment Network (Hy-CycleAlign) for robust multi-modal image alignment. It uses hyperbolic geometry to overcome challenges like distortions and appearance differences, improving fusion quality.

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    Bringing the Visible Universe into Focus with Robo-AO
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    Published on: February 12, 2013

    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

    Area of Science:

    • Computer Vision
    • Medical Image Analysis
    • Geometric Deep Learning

    Background:

    • Multi-modal image fusion requires accurate alignment, which is difficult due to nonlinear distortions and appearance variations.
    • Existing methods often struggle with complex geometric transformations and cross-modal discrepancies.

    Purpose of the Study:

    • To develop a novel framework for geometry-aware multi-modal image alignment using hyperbolic space.
    • To enhance alignment accuracy and robustness by leveraging the properties of hyperbolic geometry.

    Main Methods:

    • Introduced the Hyperbolic Cycle Alignment Network (Hy-CycleAlign), a cyclic alignment framework in hyperbolic space.
    • Employed multi-level representation embedding into a negatively curved manifold for increased sensitivity to spatial perturbations.
    • Integrated a dual-path cyclic structure for deformation consistency and a hyperbolic hierarchy contrastive alignment module for semantic and structural coherence.

    Main Results:

    • Hy-CycleAlign demonstrated superior performance in alignment accuracy, structural fidelity, and downstream fusion quality on diverse datasets.
    • Theoretical analysis confirmed that hyperbolic geometry's metric amplifies positional variations, improving misalignment discrimination.
    • The framework effectively models cross-modal correspondences despite significant challenges.

    Conclusions:

    • Hyperbolic geometric modeling offers a powerful approach for robust multi-modal image alignment.
    • Hy-CycleAlign provides a significant advancement over conventional Euclidean-space methods for complex alignment tasks.
    • The proposed method validates the effectiveness of non-Euclidean geometry in addressing challenging image alignment problems.