Multicomponent seismic data contain overlapping information on the pol
arization states of distinct body-wave modes, due to the physical proc
ess of excitation, propagation and recording. This geometric redundanc
y should be exploited to provide an accurate separation and estimation
of the wavefield attributes in order to understand the medium properl
y. This may be achieved using linear transforms, originally developed
for separating split shear waves in four-component seismic data. These
transforms separate the principal time-series components of the wavef
ield from the ray-path geometry and the orientation of the source and
geophone axes for a uniform medium; they are deterministic and can be
easily implemented. Here we reformulate the linear transforms by intro
ducing simple geometry and medium-independent matrix operators. Althou
gh for 'ideal' experiments the technique may offer nothing new to the
estimation of polarization that eigenanalysis cannot offer, neverthele
ss the formulation avoids the need to consult mathematical libraries a
nd is useful in the interpretation of the wavefield when various inevi
table acquisition-related errors dominate. Some typical problems in pr
ocessing four-component data, such as the interpretation of data matri
x asymmetry due to misorientations of the acquisition components and n
on-orthogonal polarizations for the wave components, may be easily tre
ated and identified using a common framework with this condensed matri
x form. In addition, the operation is extended to similar geometric pr
oblems in six- and nine-component data. Synthetic and held nine-compon
ent data examples are presented to illustrate the application of the m
atrix operations.