This modules allows to quickly apply a 2D-convolution 
\index{convolution}
\index{Gaussian!convolution}
to a Fimage in the 
case of a separable kernel,
$$K(x,y)=xker(x)\cdot yker(y).$$
The kernel $K$ can be given with $xker$ and $yker$ (Fsignal), or 
chosen between a constant kernel or a Gaussian kernel, both
with total mass $1$. The boundary assumption is, depending on
the value of the $b$ parameter, that
\begin{itemize}
\item $b=0$: the image is zero outside its domain
\item $b=1$: the image is symmetrized on each side 
(eg if $u>0$, $u(-i)=u(i-1)$) 
\item $b=2$: the image is periodic (eg $u(i) = u(i+n)$)
\end{itemize}
See module \verb+fconvol+ for general
convolution with non-separable 2D kernels.

\medskip

NOTE: calling this module with in=out is possible
