  Aspl{\"u}nd's metric, which is useful for pattern matching, consists in a
double-sided probing, i.e. the over-graph and the sub-graph of a function are
probed jointly. It has previously been defined for grey-scale images using the
Logarithmic Image Processing (LIP) framework. LIP is a non-linear model to
perform operations between images while being consistent with the human visual
system. Our contribution consists in extending the Aspl{\"u}nd's metric to
colour and multivariate images using the LIP framework. Aspl{\"u}nd's metric is
insensitive to lighting variations and we propose a colour variant which is
robust to noise.
