Calculation of sampling rate and its effect on an Image?

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The Nyquist theorem states that the sampling frequency (Fs) must be at least twice the maximum frequency (Fm) of a signal, which applies to both 1D signals and 2D images. To calculate the sampling frequency for a 2D image, one must consider the image's dimensions and the maximum frequency of changes in brightness across those dimensions. Over-sampling can lead to increased data without significant quality improvement, while under-sampling can cause aliasing, where high-frequency details are misrepresented. In the context of video, the frame rate (fps) must be sufficient to capture changes in luminosity to avoid visual artifacts. Understanding these principles is crucial for effective image and video processing.
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I know that for a given signal, the sampling frequency Fs must be twice or more than maximum frequency of the signal Fm. It is easy to understand the concept for a 1D signal. But I don't know how to calculate sampling frequency or Nyquist rate for a 2D image.

Also what is effect of over-sampling and under-sampling in case of image (dimensions width⋅height=204⋅226)?
 

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For video your sampling rate is frame rate per second, or fps 24, 30 etc. Size of the image is second derivation in this case, and it defines ADC conversion rate in elements per second, when all elements taken in the same time snapshot.
Over- and under-sampling has same effect as in 1D , you 'd have aliasing effect if fps lower than frequency of luminosity changes F(lm) of the object on a screen, when visible changes in brightness corresponds to beating fps and F(lm).
 
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