A channel- adaptive and plug-and- play framework for hyperspectral image analysis

Taiqin Chen, Hao Sha, Yifeng Wang, Yuan Jiang, Shuai Liu, Zikun Zhou, Ke Chen, Yongbing Zhang

Abstract: Highlights•A novel channel-adaptive framework for hyperspectral image analysis is presented by introducing a fusion strategy.•A low-rank guided attention module (LGAM) is proposed to facilitate extracting representative features.•The proposed method achieves state-of-art performance compared with existing methods on five datasets.•Our method can be a plug-in to combine with existing methods to make them channel-adaptive and boost their performance.

External IDs:dblp:journals/inffus/ChenSWJLZCZ26