Digital BW, The Print

> From: Roy Harrington
>
> Here's another way to look at it.  At the low end say the A/D is
> distinguishing between
> a value of 1 and 2.  No matter how many samples you average
> together you'll
> get either 1 or 2 since it's integer math.  This is quite
> different than in the upper
> range.  E.g. say you are distinguishing between 100100 and 100200
> where the
> bottom 2 digits are in the noise.  If you average 10 samples
> you'll be close to being
> able to distinguish 100140 and 100150.  The point being that if
> its in the bottom
> bit the multiple-sample noise reduction doesn't get represented.

The averaging I'm talking about takes place in your eye or brain. Across a
large number of pixels, even if the pixels are all 1's and 2's, you can
still represent in-between values like 1.5 or 1.123, by varying the
proportion of 1's and 2's. You just can't do it for an individual pixel. For
that to work, however, there has to be enough noise to cause dithering,
i.e., to break up any posterization.

Look at blue sky in any digital image, and it will look like a smooth blue
gradient. Zoom way in on it and it will look like blue confetti. As long as
you're not examining individual pixels, the dithering caused by the noise
effectively increases the bit depth. (That's why GIF images work at all.)
Unfortunately, for fine detail, you need those individual pixels, and that's
where the noise limits your dynamic range.

My point is that the dynamic range we're talking about is the dynamic range
for the highest spatial frequencies, where individual pixels matter. But for
low spatial frequencies, you automatically get more dynamic range, because
the noise is mostly high frequency.

--

Ciao,               Paul D. DeRocco
Paul                mailto:pderocco@...