Aliasing is the high frequencies in original signal masquerade as low frequencies after reconstruction (due to undersampling).
The name “aliasing” comes from the fact that the high-frequency signal becomes indistinguishable from low frequency signals (they become aliases).
Example: Image
Images can be decomposed into “frequencies.” And thus is also subject to aliasing.
Spatial Aliasing Example
Here is an example of spatial aliasing on the function
:
Temporal Aliasing example
An example is the “wagon-wheel effect”:
The Nyquist-Shannon theorem states that any frequency above the Nyquist frequency (half the sampling rate) can produce an alias.