Advances in Algorithms for Hyperspectral Image Processing
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 14
Special Issue Editor
Special Issue Information
Dear Colleagues,
Hyperspectral imaging paves the way for a wide range of innovative applications. Today, it is utilized in areas such as
- Precision agriculture, enabling early detection of diseases and pests, improved input management, yield forecasting, and more;
- Ecosystem management, supporting species identification for sustainable practices, disease monitoring, biomass assessment, and tracking of environmental changes;
- Environmental monitoring, facilitating ocean observation, coastal zone assessment, and pollutant detection;
- Agri-food industry, enhancing quality control processes and enabling automated sorting;
- Cultural heritage conservation, assisting in artwork analysis, uncovering hidden structures, and characterizing materials;
- Healthcare, allowing non-invasive diagnostics, surgical guidance, and tissue examination;
- Defense and security, aiding for instance in the detection of stealth coatings and camouflage, monitoring industrial activities, and locating mines.
All these methods are highly demanding in terms of computing time and memory, as well as requiring considerable effort to collect training data.
This Special Issue aims to highlight algorithms designed for detecting anomalies, building and managing spectral databases, simulating atmospheric propagation, fusing multisource images, applying physics-based approaches, leveraging machine learning for hyperspectral imaging, and assessing hyperspectral imaging performance. Furthermore, the Issue will cover the latest theoretical and applied research.
Original contributions on the above aspects and related topics are encouraged.
Dr. Jacques Blanc-Talon
Guest Editor
Manuscript Submission Information
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Keywords
- hyperspectral imaging (HSI)
- anomaly detection
- spectral databases
- simulation of atmospheric propagation
- image fusion
- physics-based methods
- machine learning for HIS
- evaluation for HSI
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