For David Millier

Started Feb 4, 2013 | Discussions thread
Contributing MemberPosts: 571
Re: For David Millier
In reply to Lin Evans, Feb 6, 2013

Dear Lin and David and all the other ones,

there is a lot of misunderstanding and misinterpretation of the Nyquist theorem and its application to image sensors. Sorry for not reading all the posts in this thread. I may repeat some arguments which have been given by others.

The usual (and simple) explaination or formulation of the Nyquist (or Shannon Theorem) doesn't hold for an imaging sensor. The sampling scheme used in all these explainations uses infinitesimally sharp sampling windows (Dirac pulses). This is not true for an imaging sensor. A sensor is filled with "sampling windows" (called pixels) which cover an area which is comparable to the pixel pitch. A pixel has no spatial information of where a photon did excite an electron on its surface. It simply integrates over all photons. This is kind of a spatial averaging filter function. This averaging function prevents a folding from higher frequencies to lower frequencies. It reduces the contrast of structures with spatial resolution approaching the pixel pitch. Structures with higher spatial frequencies are averaged out on the pixel itself. It is not really reduced to noise but close to. That doesn't mean that some periodic structures very close to the pixel pitch (as the typical resolution charts) can't produce false spatial information. This is indeed aliasing. But a special one which happens to have some of the features of the "normal" aliasing of sine waves on a point sampling device.

Jaggies shouldn't be confused with aliasing. They simply represent the fact that sampling is done at discret positions. Even a structure with a very low spatial frequency (much lower that the pixel pitch) will show jaggies. Jagies and aliasing come from the same fact that we have a discrete sampling. But they are not the same.



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