Sampling and reconstruction are usually analyzed under
the framework of linear signal processing. Powerful tools
like the Fourier transform and optimum linear filter design
techniques, allow for a very precise analysis of the process.
In particular, an optimum linear filter of any length can be
derived under most situations. Many of these tools are not
available for non-linear systems, and it is usually difficult to
find an optimum non-linear system under any criteria. In
this paper we analyze the possibility of using non-linear filtering
in the interpolation of subsampled images. We show
that a very simple (5×5) non-linear reconstruction filter outperforms
(for the images analyzed) linear filters of up to
256×256, including optimum (separable) Wiener filters of
any size.