Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Aliasing

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...

IR Frequency Region: Fingerprint Region

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...

You might also read

Related Articles

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

Sort by

Same author

Spectral State Fusion Tree Mamba for Hyperspectral Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

DASR-Net: dual-attention scattering restoration network for imaging in turbid media via weakly supervised learning.

Optics express·2026

Same author

Signal-enhanced DOAS based on the secondary diffraction spectrum and its application in sulfur dioxide measurement.

Applied optics·2026

Same author

Analysis of the movement of permanent GNSS stations in Spain with directional statistics.

Scientific reports·2026

Same author

Domain-Adaptive Mamba for Cross-Scene Hyperspectral Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Masked Self-Attention Fusion Network for Joint Classification of Hyperspectral and LiDAR Data.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Search research articles

Related Experiment Video

Updated: Jun 14, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Anomaly Detection in Hyperspectral Images Using Adaptive Graph Frequency Location.

Bing Tu, Xianchang Yang, Baoliang He

IEEE Transactions on Neural Networks and Learning Systems

|September 2, 2024

Summary

This summary is machine-generated.

This study introduces graph frequency analysis for hyperspectral anomaly detection (HAD). The novel approach effectively integrates graph structure and spectral features, improving anomaly detection performance in hyperspectral images (HSIs).

More Related Videos

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Related Experiment Videos

Last Updated: Jun 14, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Area of Science:

Remote Sensing
Computer Vision
Graph Theory

Background:

Graph theory methods are used for hyperspectral anomaly detection (HAD).
Existing graph-based methods overemphasize graph structure and neglect spectral features in hyperspectral images (HSIs).

Purpose of the Study:

To introduce graph frequency analysis for HAD.
To integrate graph structure and spectral features effectively for improved anomaly detection.

Main Methods:

Constructing a beta distribution-based graph wavelet space for anomaly detection.
Treating anomaly detection as a graph frequency location problem.
Developing a novel entropy definition for adaptive frequency localization.

Main Results:

The proposed method leverages energy shifting to higher frequencies caused by anomalies.
Accurate extraction of anomalies by pinpointing specific Beta wavelets associated with high-frequency content.
Experimental validation on seven real HSIs demonstrated superior performance compared to state-of-the-art methods.

Conclusions:

Graph frequency analysis offers a powerful approach for HAD.
The novel method effectively combines graph structure and spectral information.
The approach shows significant improvements in detecting anomalies in hyperspectral images.