Unsupervised Classification of PolSAR Imagery via Kernel Sparse Subspace Clustering.

Unsupervised classification is very important for the fully polarimetric synthetic aperture radar (PolSAR) image interpretation. The PolSAR covariance matrices, as one of the most widely used representations for PolSAR data, are Hermitian positive definite (HPD) and form a Riemannian manifold when endowed with an appropriate metric. Considering their geometric properties, we propose a new clusteri...