@inproceedings{florencio1995post-sampling,
author = {Florencio, Dinei and Schafer, Ronald W.},
title = {Post-Sampling Aliasing Control for Natural Images},
year = {1995},
month = {May},
abstract = {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 (5x5) non-linear reconstruction filter outperforms (for the images analyzed) linear filters of up to 256x256, including optimum (separable) Wiener filters of any size.},
url = {http://approjects.co.za/?big=en-us/research/publication/post-sampling-aliasing-control-for-natural-images/},
}