Hyperspectral Image Classification via Exploring Spectral–Spatial Information of Saliency Profiles
Morphological features have shown promising performances for hyperspectral image (HSIs) classification, as they can efficiently extract the multilevel spatial information of HSIs. However, the objects in the scenes are always with different sizes and shapes, making it difficult to excavate spatial i...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9119757/ |