Pascal Castellazzi

1paper

1 Paper

MLAug 8, 2020
$k$-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences

Daniel Fryer, Hien Nguyen, Pascal Castellazzi

We state theoretical properties for $k$-means clustering of Symmetric Positive Definite (SPD) matrices, in a non-Euclidean space, that provides a natural and favourable representation of these data. We then provide a novel application for this method, to time-series clustering of pixels in a sequence of Synthetic Aperture Radar images, via their finite-lag autocovariance matrices.