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 …

Sparse recovery in magnetic resonance imaging with a Markov random field prior

Augmented Lagrangian based reconstruction of non-uniformly sub-Nyquist sampled MRI data