Howtosignalprocessing
- What does the Nyquist theorem determine?
- What does the Nyquist theorem tell us about sample rate?
- What does the Nyquist frequency represent?
- What is Nyquist theorem and what it's relevance to image processing?
What does the Nyquist theorem determine?
The Nyquist theorem defines the minimum sample rate for the highest frequency that you want to measure. The Nyquist rate is 2x the given frequency to be measured accurately. The theorem can be used in reverse.
What does the Nyquist theorem tell us about sample rate?
This theorem states that the highest frequency which can be represented accurately is one half of the sampling rate. The Nyquist rate specifies the minimum sampling rate that fully describes a given signal; in other words a sampling rate that enables the signal's accurate reconstruction from the samples.
What does the Nyquist frequency represent?
The Nyquist frequency is a type of sampling frequency that uses signal processing that is defined as “half of the rate” of a discrete signal processing system. It is the highest frequency that can be coded for a particular sampling rate so that the signal can be reconstructed.
What is Nyquist theorem and what it's relevance to image processing?
The Nyquist theorem states that when sampling a signal (such as the conversion from an analog image to a digital image), the sampling frequency must be greater than twice the frequency of the input signal so that the reconstruction of the original image will be as close to the original signal as possible.
