Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral Images

A novel unfolding approach for clustering hyperspectral images by transforming an ADMM-based sparse subspace clustering algorithm into a neural network architecture to obtain the self-representation matrix, while incorporating structural priors to preserve the data structure.