The (uncentred, unnormalised)
spatial covariance function of a pixel image \(X\) in the plane
is the function \(C(v)\) defined for each vector \(v\) as
$$
C(v) = \int X(u)X(u-v)\, {\rm d}u
$$
where the integral is
over all spatial locations \(u\), and where \(X(u)\) denotes the
pixel value at location \(u\).
This command computes a discretised approximation to
the spatial covariance function, using the Fast Fourier Transform.
The return value is
another pixel image (object of class "im"
) whose greyscale values
are values of the spatial covariance function.
If the argument Y
is present, then imcov(X,Y)
computes the set cross-covariance function \(C(u)\)
defined as
$$
C(v) = \int X(u)Y(u-v)\, {\rm d}u.
$$
Note that imcov(X,Y)
is equivalent to
convolve.im(X,Y,reflectY=TRUE)
.