Riemannian geometry for Compound Gaussian distributions: application to recursive change detection

05/20/2020
by   Florent Bouchard, et al.
0

A new Riemannian geometry for the Compound Gaussian distribution is proposed. In particular, the Fisher information metric is obtained, along with corresponding geodesics and distance function. This new geometry is applied on a change detection problem on Multivariate Image Times Series: a recursive approach based on Riemannian optimization is developed. As shown on simulated data, it allows to reach optimal performance while being computationally more efficient.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset