N
Neil Gould
Hi,
From your own response to an earlier post:
"With a drum scanner the spot size (and it's shape) is the anti-alias
filter, and the only one that is needed. One of the most useful features
of most drum scanners is that the spot size can be adjusted independently
of the sampling density to obtain the optimum trade-off between resolution
and aliasing..."
^^^^^^^^^^^^^^^^^^^^^^^^^
In another post, you reported:
"then the photomultiplier in the scanner produces a signal which is
proportional to the average illumination over
the area of the spot."
Sounds (and looks) like distortion to me, given that the "area of the
spot" may have more than one illumination level, and the recorded value is
averaged. ;-)
"identitiy". I've not heard the term used in such a way that it includes a
"less than" clause. ;-)
output representation artifacts, as are "lumpies" or other kinds of
distortions dependent on the representation of the pixels identified in
the numeric data resulting from sampling. My claim is that the numeric
data contains various distortions of the subject, and while some may be
assignable to the input filtering (including those you mentioned), but
others are assignable to the practical limitations of math operations, and
that these errors are inextricable.
be:
"However, since the grain is random and smaller than the spot size, each
aliased grain only extends over a single pixel in the image - but this can
be many times larger than the actual grain on the original. "
IOW, the measure of the subject is not "infinitesimally small", and by
your own admission, some aspects of the subject (e.g. minimum grain sizes)
can be smaller than the sample size.
I agree with those statements in your posts, even if you don't! ;-)
artifacts as rounding errors, for example?
real-world recording processes. The reason that I stressed how _audio_ is
recorded -- as opposed to the burning of the end result onto a CD
master -- is that the first stages of the recording process is somewhat
more analogous to scanning than "recording a CD".
MANY artifacts are introduced because of the lack of, as you have put it,
an adequate input filter. There is not a microphone made that will capture
actual acoustic events due to many factors, not the least of which is that
those events are typically not two dimensional in nature, but the
processes of the capturing devices (microphones) are. The rest of the
recording process is one of manipulation and error correction to create an
acceptable representation of the original acoustic events. I've not run
into anyone "in the biz" that would claim that these two are "in
identity", or that it would be possible to reconstruct the original
acoustic events from the sampled data (recording).
Finally, the process of reducing the recorded data to the 44.1/16 standard
introduces MORE errors by virtue of whether dithering is used, and if so,
which dithering algorithms one chooses. By the time a CD is ready for
purchase, it's much more akin to a painting than a scanned photograph,
which is why I think it was a poor choice as an example for this topic.
world implementations, as film in hand represents just that. I don't have
a problem with the theory, and not only understand it, but agree that *in
theory* the math behind sampling can lack distortion. However, I don't
live in theory, and have little real-world use for theoretical "solutions"
that can't be (or at least, aren't) realized. ;-)
To that end, I think I'll just rely on the results I've been able to
obtain. I, as I presume the OP, am interested in understanding the
limitations of the process. Your own posts have provided excellent bases
for the understanding of such limitations. What puzzles me is that you
don't see the "trade offs" that you spoke of as distortions of the
original subject. What, exactly, are you "trading off" that doesn't result
in a reduction of the available data in the subject?
every stage of the real-world process as introducing errors, and thus
distortions of the subject.
input filtering and flawlessly applies sampling algorithms, all that is
left is to expand my knowledge by being presented with such a system. ;-)
filters (e.g. the implementation). I'm only concerned about systems. So
there's no "about face" involved, we're just interested in different
things, it seems. ;-)
Regards,
In which case, I disagree with your usage of the term "identity".Recently said:No, however the sampled data is in identity with the subject *after*
it has been correctly filtered at the input stage.
The principle is not where the problem lies. It is in the implementation.This principle is
the entire foundation of the sampling process. No information can
get past the correct input filter which cannot be accurately and
unambiguously captured by the sampling system.
"Accurately and unambiguously" = "No distortion".
From your own response to an earlier post:
"With a drum scanner the spot size (and it's shape) is the anti-alias
filter, and the only one that is needed. One of the most useful features
of most drum scanners is that the spot size can be adjusted independently
of the sampling density to obtain the optimum trade-off between resolution
and aliasing..."
^^^^^^^^^^^^^^^^^^^^^^^^^
In another post, you reported:
"then the photomultiplier in the scanner produces a signal which is
proportional to the average illumination over
the area of the spot."
Sounds (and looks) like distortion to me, given that the "area of the
spot" may have more than one illumination level, and the recorded value is
averaged. ;-)
Which only further reinforces my disagreement with your usage ofIf properly filtered prior to sampling then the sampled data is a
*perfect* representation of the filtered subject. In short, there may be
*less* information in the properly sampled and reconstructed subject
than in the original, but there can never be more.
"identitiy". I've not heard the term used in such a way that it includes a
"less than" clause. ;-)
I didn't suggest that jaggies are aliasing artifacts. They are clearlyHowever imperfect
reconstruction will result in artefacts and distortion which are not
present in the original subject - false additional information, and
jaggies fall into this category, they are not aliasing artefacts.
output representation artifacts, as are "lumpies" or other kinds of
distortions dependent on the representation of the pixels identified in
the numeric data resulting from sampling. My claim is that the numeric
data contains various distortions of the subject, and while some may be
assignable to the input filtering (including those you mentioned), but
others are assignable to the practical limitations of math operations, and
that these errors are inextricable.
As you present in another post, the issue relevent to the topic appears toEach sample
represents a measure of the subject at an infinitesimally small point
in space (or an infinitesimally small point in time).
be:
"However, since the grain is random and smaller than the spot size, each
aliased grain only extends over a single pixel in the image - but this can
be many times larger than the actual grain on the original. "
IOW, the measure of the subject is not "infinitesimally small", and by
your own admission, some aspects of the subject (e.g. minimum grain sizes)
can be smaller than the sample size.
Not according to your own posts (as excerpted, above).Sorry Neil, but that is completely wrong.
I agree with those statements in your posts, even if you don't! ;-)
I see. And, just what kind of system are you using that avoids suchThat, most certainly, is *NOT* a fact! Whilst I am referring to an
interpretation of the sampled data, the correct interpretation does
*not* introduce distortion. You appear to be hung up on the false
notion that every step introduces distortion - it does not.
artifacts as rounding errors, for example?
Our disagreement boils down to whether artifacts are introduced byNo, that is the Red Book specification - I suggest you look it up -
how yo get to that sampled data is irrelevant to the discussion on the
reconstruction filter.
real-world recording processes. The reason that I stressed how _audio_ is
recorded -- as opposed to the burning of the end result onto a CD
master -- is that the first stages of the recording process is somewhat
more analogous to scanning than "recording a CD".
MANY artifacts are introduced because of the lack of, as you have put it,
an adequate input filter. There is not a microphone made that will capture
actual acoustic events due to many factors, not the least of which is that
those events are typically not two dimensional in nature, but the
processes of the capturing devices (microphones) are. The rest of the
recording process is one of manipulation and error correction to create an
acceptable representation of the original acoustic events. I've not run
into anyone "in the biz" that would claim that these two are "in
identity", or that it would be possible to reconstruct the original
acoustic events from the sampled data (recording).
Finally, the process of reducing the recorded data to the 44.1/16 standard
introduces MORE errors by virtue of whether dithering is used, and if so,
which dithering algorithms one chooses. By the time a CD is ready for
purchase, it's much more akin to a painting than a scanned photograph,
which is why I think it was a poor choice as an example for this topic.
And, is in fact, one of the issues at the root of my perspective. ;-)Of course, this approach assumes that the entire image can be
adequately represented in 3000 or 2000ppi, which may not be the case,
just as many audiophiles clamour for HD-CD media to met their higher
representation requirements.
The crux of the matter is that I'm only interested in what happens in realYour assertion that the sampled data is inherently distorted and that
this inevitably passes into the reproduction is in complete
disagreement with Claude Shannon's 1949 proof. I suggest that you
will need much more backup than a simple statement of disagreement
before many people will take much notice of such an unfounded
allegation.
world implementations, as film in hand represents just that. I don't have
a problem with the theory, and not only understand it, but agree that *in
theory* the math behind sampling can lack distortion. However, I don't
live in theory, and have little real-world use for theoretical "solutions"
that can't be (or at least, aren't) realized. ;-)
To that end, I think I'll just rely on the results I've been able to
obtain. I, as I presume the OP, am interested in understanding the
limitations of the process. Your own posts have provided excellent bases
for the understanding of such limitations. What puzzles me is that you
don't see the "trade offs" that you spoke of as distortions of the
original subject. What, exactly, are you "trading off" that doesn't result
in a reduction of the available data in the subject?
I "had it" long before your first posts on the subject. However, I seeGood God, I think he's finally got it, Watson! The spot is part of
the input filter of the sampling system, just as the MTF of the
imaging optics are!
every stage of the real-world process as introducing errors, and thus
distortions of the subject.
As, to my knowledge, there is no system available that implements perfectIndeed these components (optics, spot etc.) can be used without
sampling in the signal path at all, as in conventional analogue TV,
and will result in exactly the same distortions that you are
referring to. If this is not proof that sampling itself does not
introduce an inherent distortion then I do not know what is!
input filtering and flawlessly applies sampling algorithms, all that is
left is to expand my knowledge by being presented with such a system. ;-)
I'm not terribly concerned about sampling (e.g. the math) without inputJust in case you haven't noticed, you have in the above statement
made a complete "about-face" from your previous statements - you are
now ascribing the distortions, correctly, to the input filter not the
sampling process itself, which introduces *no* distortion, or the
reconstructon filter which can introduce distortion (eg. jaggies) if
improperly designed.
filters (e.g. the implementation). I'm only concerned about systems. So
there's no "about face" involved, we're just interested in different
things, it seems. ;-)
Regards,