S$^2$Mamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification

arXiv:2404.18213v1 Announce Type: new
Abstract: Land cover analysis using hyperspectral images (HSI) remains an open problem due to their low spatial resolution and complex spectral information. Recent studies are primarily dedicated to designing Transformer-based architectures for spatial-spectral long-range dependencies modeling, which is computationally expensive with quadratic complexity. Selective structured state space model (Mamba), which is efficient for modeling long-range dependencies with linear complexity, has recently shown promising progress. However, its potential in hyperspectral image processing that requires handling numerous spectral …

arxiv classification cs.ai cs.cv image mamba space spatial state state space model type