Pyramid Hierarchical Transformer for Hyperspectral Image Classification

arXiv:2404.14945v1 Announce Type: new
Abstract: The traditional Transformer model encounters challenges with variable-length input sequences, particularly in Hyperspectral Image Classification (HSIC), leading to efficiency and scalability concerns. To overcome this, we propose a pyramid-based hierarchical transformer (PyFormer). This innovative approach organizes input data hierarchically into segments, each representing distinct abstraction levels, thereby enhancing processing efficiency for lengthy sequences. At each level, a dedicated transformer module is applied, effectively capturing both local and global context. Spatial and spectral information flow within …

abstract abstraction arxiv challenges classification concerns cs.cv data efficiency hierarchical image pyramid scalability transformer transformer model type