Aliasing happens when “too few samples steal high frequencies and disguise them as low ones.”
1. What is aliasing in a sampled image?
2. In two-dimensional rectangular sampling, which expression gives the sampled image values?
3. What sampling condition does the Nyquist-Shannon theorem impose to prevent spectral overlap and aliasing?
Sampling model — formula?
Discrete sampled function: $f_d(m,n)=f(m riangle x,n riangle y)$.
Aliasing — cause?
Under-sampling causes high frequencies to appear as low ones.
Discrete sampled function
Sampled at regular grid points in space.
Aliasing
Falsely low frequency artefacts from under-sampling.
Nyquist theorem
Prevents aliasing with proper sampling rate.
Nyquist frequency
Half the maximum original frequency.
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