Advanced Hyperspectral Imaging: Techniques, Data Analysis, and Applications
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Color, Multi-spectral, and Hyperspectral Imaging".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 368
Special Issue Editor
Interests: hyperspectral imaging; remote sensing; machine vision; computer vision; statistical machine learning; artificial intelligence
Special Issue Information
Dear Colleagues,
Hyperspectral imaging (HSI) technology has been one of the most effective techniques for the identification of targets from heavily cluttered backgrounds across industrial, agricultural, environmental monitoring, and defence/military sectors. Like other technologies, cutting-edge HSI research has evolved into using deep learning (DL) and artificial intelligence (AI) for enhancing imaging hardware, particularly its snap-shot multispectral form, and hyperspectral imagers; it is also used for data analysis to detect subpixel targets that are embedded in scenes with complicated geographical, vegetation, and textual-rich backgrounds. While conventional techniques such as compressive sensing, data integrity enhancements using multivariate analysis, and target detections through likelihood approaches have been very successful for many practical applications, AI-based methods and their combination with conventional model-based methodologies have emerged, being increasingly successful from the perspective of target detection.
This Special Issue addresses the use of DL and AI for solving real world problems, particularly for long range target detections with a high degree of universality; articles and reviews on this subject are highly welcome. Particular interests include, but are not limited to, the following: multiplex image-acquisition techniques, super-resolutions, supervised or unsupervised target detections, transfer learning, band selections, network optimizations, and self-organized DL. Direct comparisons of the effectiveness of AI versus conventional model-based methodologies are also highly sought.
Dr. Peter Yuen
Guest Editor
Manuscript Submission Information
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Keywords
- hyperspectral imaging
- remote sensing
- deep learning
- artificial intelligence
- multiplex image-acquisition techniques
- super-resolutions
- supervised or unsupervised target detection
- band selections
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