Most sampled imaging systems produce aliasing. That is, the sampling process causes spatial frequencies beyond the system's sampling passband to fold into spatial frequencies within the sampling passband. In this way, sampling can produce potentially significant image artifacts, particularly if digital filtering is used to restore (`deconvolve,' high-boost filter) the aliased, sampled image data prior to reconstruction. In this paper we use a model-based computational simulation to process natural scenes in a way that enables the restoration-enhanced `aliased component' of the reconstructed image to be isolated and displayed unambiguously.
Stephen K. Park,
"Image restoration versus aliased noise enhancement", Proc. SPIE 2239, Visual Information Processing III, (24 June 1994); doi: 10.1117/12.179296; https://doi.org/10.1117/12.179296