FUSION

From model-based optimization algorithms to deep learning models for clustering hyperspectral images

Hyperspectral images (HSIs), captured by different Earth observation airborne and space-borne systems, provide rich spectral information in hundreds of bands, enabling far better discrimination between ground materials that are often …

Subspace clustering for hyperspectral images via dictionary learning with adaptive regularization

Sparse subspace clustering (SSC) has emerged as an effective approach for the automatic analysis of hyperspectral images (HSI). Traditional SSC-based approaches employ the input HSI data as a dictionary of atoms, in terms of which all the data …

A robust sparse representation model for hyperspectral image classification