If you look at the depth of field equations, they are based on whether
the circle of confusion is smaller than the size of the pixel. When you
look at an image on the web (generally about 2MP or below) the effective
dof is a lot greater than if you pixel peep the raw file (16-24 MP or
more), because the smaller files can handle a lot larger circle of
confusion than the raw image.
It seems to me that with sensors so high resolution that they are
diffraction limited at f/5.6 or so, that it would be possible for image
processing software to detect the increasing circle of confusion (at 2
or 3 pixels) with a lot more accuracy than our eyes can, and could
therefore more accurately enhance the effects of depth of field than
just applying a blur to the background of an image.
Likewise, given a good model of the lens (bokeh) it might also be
possible to mathematically increase the depth of field.
A corollary to this is that it would in theory be possible to extract
depth/distance information from the image (though it might be hard to
tell the difference between something being 2 times the focal distance
and 1/2 the focal distance.
Are there any hard core signal/image processing nerds on the list who
know anything about work being done on this? It wasn't too long ago
that it would take the sort of processing that only Los Alamos or the
NSA had to do this, but desktop computers are probably running something
like 2005 "Craymarks", particularly with GPUs.
--
Larry Colen l...@red4est.com (postbox on min4est) http://red4est.com/lrc
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