[opendtv] Re: 20060117 Mark's (Almost) Monday Memo
- From: Craig Birkmaier <craig@xxxxxxxxx>
- To: opendtv@xxxxxxxxxxxxx
- Date: Tue, 24 Jan 2006 08:49:21 -0500
At 5:23 PM -0500 1/21/06, Albert Manfredi wrote:
>
>I believe you are referring to the Nyquist limit here. That
>does apply to images, of course. But Shannon's Law refers
>to the limiting bit rate that can be transferred in a given
>channel width, as a function of signal to noise ratio. The
>analogous limit in image compression might be stated as
>"given the pixel count, frequency content, color content, of
>a given image, what is the smallest file size that can be
>achieved, in theory (i.e. not restricted to any existing
>algorithm), with no loss of image information?
Sorry for the confusion. I was thinking about Shannon's sampling
theorem, which does involve the Nyquist limit.
This raises an interesting point. Shannon's Law does overlap with
video compression theory, as various forms of lossless entropy coding
are used to deal with the huge number of bits that are delivered when
compressing video.
As you correctly assert, there are well known limits on how much you
can crunch any bitstream without introducing errors. Lossless video
compression may be an important tool if the application demands a
lossless coding system,. say for acquisition or post production
special effects work. But this is largely irrelevant to emission
coding; most digital acquisition systems use lossy coding today; HDV
uses MPEG-2 long GOP coding.
Modern video compression techniques rely upon the ability to
selectively lose some information, based on the "theory" that the
human visual system cannot process all of the information in motion
imaging streams, and that small errors will be difficult to perceive.
In this context, Shannon's Law has little relevance to the
discussion, but his sampling theorem is highly relevant, as it
provides the basis for determining how accurate the initial sampling
is, and how much entropy there is in any given image sequence, that
can be eliminated.
Regards
Craig
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