Abstract
To overcome the limitations of HSIs in achieving precise classification and the inability of MSIs to provide rich spectral information, a sub-pixel super-resolution model based on dictionary learning and an adaptive deep-learning-based mapping model are proposed in this part for the collaborative utilization of MSIs and HSIs, and fully leverage the high spectral resolution of HSIs and the large swath width and high spatial resolution of MSIs, ultimately achieve high-spatial-resolution HSIs in large-scale scenes.
| Original language | English |
|---|---|
| Title of host publication | Machine-Learning-Based Hyperspectral Image Processing |
| Publisher | wiley |
| Pages | 87-127 |
| Number of pages | 41 |
| ISBN (Electronic) | 9781394267880 |
| ISBN (Print) | 9781394267859 |
| DOIs | |
| State | Published - 1 Jan 2026 |
| Externally published | Yes |
Keywords
- Collaborative utilization
- Deep learning
- Dictionary learning
- Hyperspectral images
- Multispectral images
- Super-resolution
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