This article primarily aims to unify the various formalisms of multivariate
coefficients of variation, leveraging advanced concepts of generalized means,
whether weighted or not, applied to the eigenvalues of covariance matrices. We
highlight the existence of an infinite number of these coefficients and
demonstrate that they are bounded. Moreover, we link the various coefficients
of variation identified in the literature to specific instances within our
unified formalism. We illustrate the utility of our method by applying it to a
time series of polarimetric radar imagery. In this context, the coefficient of
variation emerges as a key tool for detecting changes or identifying permanent
scatterers, which are characterized by their remarkable temporal stability. The
multidimensionality arises from the diversity of polarizations. The
introduction of the various possible coefficients demonstrates how their
selection impacts the detection of samples exhibiting specific temporal
behaviors and underscores the contribution of polarimetry to dynamic speckle
analysis