Let's consider some dither noise patterns.
One simple type of noise is called uniform or white noise.
White noise generates values within an interval such that all outcomes are equally likely.
Here we add zero-mean white noise to our image.
The term zero-mean indicates that the average value of the noise is zero.
This will assure that our dithering does not change the apparent brightness of our image.
The only thing left to specify is the range of noise values, this is called the noise's
amplitude. The amplitude that makes the most sense is the spacing between thresholds.
This is not, however a requirement. It is rare to specify a larger amplitude (Why?), but
frequently slightly smaller amplitudes are used. Let's look back at our example to see what
random noise dithering looks like.
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The result is not a good as expected.
The noise pattern tends to clump in different regions of the image.
The unsettling aspect of this clumping is that it is unrelated to the image.
Thus the dithering process adds apparent detail to the image that are not really in the image.
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