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Re: A lot of people don't understand dither

*** What Todd correctly points out is that if the original signal contains wideband noise, with a suitable distribution, and at a level at or above the target word length's equivalent noise floor, then the signal is self-dithering and truncation to the target length can be done without additional dither. ***

Typical ambient noise levels captured by the mic is not sufficiently random and also too high to produce self dithering (you can analyze the spectrum to see what I mean). However, the self dithering comes from the decimation process in a sigma delta ADC. In that respect, what Todd originally said is strictly speaking not correct.

As for truncating to the target length, if you do that without dither it will not be as good as using dither, as per my analogy with reducing the color depth of a picture.

Again, ambient noise levels are not necessarily random in either amplitude or spectral content - hence the phenomenon of our ears apparently being able to hear "below the noise floor".

*** Your 24bit/16bit picture analogy is not quite valid as truncation to 16 bit (i.e. 5/6/5 bits for R/G/B respectively) makes the target noise floor exceed that part of the noise floor in the original image that could have worked as self-dither. ***

Try it yourself. Select an image (you can use a noisy image if you like). Using software of your choice, reduce the color depth from 24-bits to 16-bits with and without dither and then compare the results. Your eyes will notice banding if dither is not used.

Hint for generating an image with a lot of color noise - try shooting with a high ISO (which amplifies the CCD signal) in very dark conditions using long exposure. You will find the noise levels to easily exceed 16-bit (5/6/5) resolution. And yet, dithering from 24 to 16 reduces banding. This is independent of the noise level of the original image, as I originally pointed out.

The analogy back to audio is that dithering will reduce the "banding" caused in quantization noise caused by truncation regardless of the noise floor of the original signal.

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