Calculation of sampling rate and its effect on an Image?

In summary, the conversation discusses the importance of the sampling frequency Fs being at least twice the maximum frequency Fm for a given signal. While this concept is easily understood for 1D signals, it becomes more complicated when dealing with 2D images. The dimensions and size of the image determine the ADC conversion rate, which is similar to the sampling rate for video (frame rate per second). Over- and under-sampling in the context of images have the same effect as in 1D, causing aliasing if the frame rate is lower than the frequency of luminosity changes of the object on the screen.
  • #1
ramdas
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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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  • #2
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).
 

Related to Calculation of sampling rate and its effect on an Image?

1. What is sampling rate and how does it affect an image?

The sampling rate refers to the frequency at which an image is digitized or sampled. It determines the number of samples taken per unit of time, which can affect the quality and clarity of an image. A higher sampling rate allows for more detail and accuracy in the image, while a lower sampling rate may result in a loss of detail and blurriness.

2. How is sampling rate calculated?

Sampling rate is typically calculated by dividing the total number of samples by the total time taken to capture those samples. For example, if 1000 samples were taken in 10 seconds, the sampling rate would be 100 samples per second.

3. What factors can affect the optimal sampling rate for an image?

The optimal sampling rate for an image can be affected by various factors such as the resolution of the image, the type of image sensor used, the complexity of the image, and the intended use of the image. Generally, a higher resolution image will require a higher sampling rate to capture all the details accurately.

4. How does undersampling and oversampling impact an image?

Undersampling occurs when the sampling rate is too low, resulting in a loss of detail and accuracy in the image. On the other hand, oversampling refers to a sampling rate that is higher than necessary, which can lead to larger file sizes and longer processing times without significantly improving the image quality.

5. Can the sampling rate be changed after an image has been captured?

No, the sampling rate cannot be changed after an image has been captured. It is determined by the hardware and software used to capture the image. However, the resolution of an image can be adjusted, which can indirectly affect the sampling rate by altering the number of pixels in the image.

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