[opendtv] Re: Precision

The discussion seems to dwell on the type of resolution sometimes referred
to as "fine line" resolution -- i.e. how small a detail can be reproduced.
An important type of resolution in displays is "edge" resolution -- i.e. how
accurately a diagonal line can be positioned and how well well "jaggies" can
be suppressed.  This doesn't involve extended frequency response, but rather
accurate phase response of the frequency components of the video image.  Jim
Davis out at RCA avionics in Van Nuys, CA pointed this out in a patent I
filed for him 35 years ago or so, as I recall.

Fewer lines in the display hurts the angular resolution of an edge and
lowers the step frequency making jaggies more visible.  The human visual
system is quite sensitive to jaggies.  We  easily espy low-spatial-frequency
parts of a display being out of correct spatial or temporal position, while
superposed random noise is largely disregarded.

Video compression may have fewer problems with accurately defining phase
response of the moving edge than with defining moving fine line detail.

Al

----- Original Message ----- 
From: "Craig Birkmaier" <craig@xxxxxxxxx>
To: <opendtv@xxxxxxxxxxxxx>
Sent: Monday, May 28, 2007 1:39 PM
Subject: [opendtv] Re: Precision


> At 12:41 PM -0400 5/28/07, Tom Barry wrote:
> >All this is good but it would seem there would also be a point where
> >you don't need any noise or dithering because you were storing and
> >displaying sufficient colors/bits such that the HVS could not see
> >the difference anyway.  Just on principle I'd like to get to that
> >point.
> >
> >And I worry that once you add (or keep) noise it becomes
> >information, subtracting from the available bit budget.  We already
> >live with this in the various film grain debates that pop up
> >periodically.
>
> In theory this sounds wonderful. But in practice it is difficult to
achieve.
>
> The whole point of using digital video compression is to:
>
> 1. Remove redundancy - this is why temporal coding typically
> contributes significantly more coding gain than spatial coding. If
> done well this can be virtually lossless.
>
> 2. Substitute correlated noise for picture information - this is what
> we do when we quantize away high frequency image details. This is
> ALWAYS lossy.
>
> Bottom line, the better we can do at predicting what adjacent frames
> look like, the more bits we have to preserve the high frequency
> details.
>
> Regards
> Craig
>
>
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