Model-Driven, Data-Driven and Symmetry Methods in Hyperspectral Image Processing
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 1292
Special Issue Editors
Interests: hyperspectral image processing; computer vision; machine learning
Special Issue Information
Dear Colleagues,
Image and spectra are the two essential bases that people use to recognize and distinguish between objects in the real world. Images provide a basis to solve geometric problems related to geographical objects, and spectra reflect the unique physical properties of these geographical objects. Hyperspectral images (HSIs) play an increasingly important role in various fields, such as remote sensing, object detection, and medical examination. In recent years, model-driven, data-driven, and symmetry technologies have attracted much attention with regard to the field of HSI processing. This Special Issue aims to discuss new model-driven, data-driven, and symmetry methods that can solve problems related to HSI processing. By launching this Special Issue, we hope to promote the development of corresponding models and algorithms. Therefore, researchers who work in areas related to these research fields are encouraged to contribute papers for publication in this Special Issue.
Dr. Yong Chen
Dr. Yu-Bang Zheng
Guest Editors
Manuscript Submission Information
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Keywords
- remote sensing
- multispectral/hyperspectral image processing
- restoration, reconstruction, and fusion
- saliency detection and anomaly detection
- application in remote sensing
- optimization modeling
- machine learning and deep learning
- symmetry
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