For digital images, noise is assumed to be additive gaussian white noise. I remember noise in images is considered as high frequency. However, from the link https://en.wikipedia.org/wiki/White_noise, it says
a random signal is considered "white noise" if it is observed to have a flat spectrum over the range of frequencies that is relevant to the context.
Does it mean frequencies of noise will extend from low frequencies to high frequencies? Why do we try to only remove high frequency component? Is human visual system not sensitive to low frequency noise?
From the same link, https://en.wikipedia.org/wiki/White_noise
In digital image processing, the pixels of a white noise image are typically arranged in a rectangular grid, and are assumed to be independent random variables with uniform probability distribution over some interval.
It reads that the pixels of a white noise image are assumed to be independent random variables with uniform probability distribution over some interval. Does it mean that one pixel and its neighbors are i.i.d?