Advances in Hyperspectral Remote Sensing Image Anomaly Detection
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 9
Special Issue Editors
Interests: object detection and tracking; image processing; remote sensing; machine learning; pattern recognition
Interests: hyperspectral image; snomaly detection; target detection; remote sensing image processing; deep learning; machine learning
Special Issue Information
Dear Colleagues,
Hyperspectral imaging technology, with its excellent spectral imaging technology, has become one of the core technologies in fields such as environmental monitoring, mineral exploration, and smart agriculture. In this technology, hyperspectral anomaly detection, as one of the core technologies of the Earth observation system, can detect anomaly targets that differ significantly from the surrounding spectral environment without prior spectral information. These anomaly targets may represent potential targets, environmental threats, or other critical information. Their precise detection has important scientific and practical value.
This Special Issue focuses on cutting-edge technologies in hyperspectral anomaly detection, covering innovative algorithms, robustness methods, and practical application research. We encourage submissions that focus on the following challenges:
- Hyperspectral anomaly detection and tracking methods based on probability statistics, representation, and deep learning;
- Detection and tracking techniques for missing or scarce annotated data;
- Real-time or big data processing technology for spaceborne or unmanned aerial vehicles;
- Typical application technologies in agriculture, the environment, disaster emergencies, and other fields.
Prof. Dr. Huixin Zhou
Dr. Pei Xiang
Dr. Chuan Fu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- hyperspectral image
- anomaly detection
- object tracking
- machine learning
- deep learning
- remote sensing
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