Aliasing in Images

Have you ever come across an image like above? You can notice that in the top part we don’t see a chess pattern and pixels are somewhat not that clear as in the bottom part. Ever wondered what’s causing this? To explain this phenomenon let us take an example in 1 dimension. Let us consider a sin wave-

If we take some points on this sin wave-

We can notice that we are having an adequate number of points (samples)in a wave. That is if we join the samples in a smooth manner, we can easily construct the original sine wave. Now look at the second sine wave, there are not many points(samples) available. If we join the points to obtain a sine wave, we get a low-frequency sine wave. Much of the information of the original signal is lost. This is aliasing .“Signals that travel in disguise as other frequencies are called aliased signals.”
As we know that images are signals in 2 DIMENSION, so aliasing in images is what you saw in the image at the top. When we are not having enough samples or pixels to represent the information that is in high frequency. We can see this phenomenon more prominently in a chirp-

Here are few more examples showing aliasing in images:-


In my next post I ll tell you about how to remove aliasing from the images. Till then THANK YOU.
