From: Philippe Verdy (verdy_p@wanadoo.fr)
Date: Thu May 05 2005 - 11:53:32 CDT
----- Original Message -----
From: "Elliotte Harold" <elharo@metalab.unc.edu>
Cc: "Unicode List" <unicode@unicode.org>
Sent: Thursday, May 05, 2005 2:02 PM
Subject: Re: Data compression
> Barring independent verification, I'm skeptical of the claim.
I would be too, if that searcher had not already called for the service of
an independant evaluation, and based on his report, obtained funding in the
Australian stocks exchange.
> Data compression is a field second only to encryption in the amount of
> snake oil that's come and gone over the last couple of decades. This is
> not the first time I've heard spectacular claims made for new compression
> systems only to never see them actually reach the market. At least with
> compression it tends to be really obvious that a system doesn't work. With
> data encryption sometimes the flaws aren't as readily apparent.
>
> Perhaps this researcher really has found a technique everybody else
> missed. But I'll believe it once I see a shipping product. Until then I
> remain skeptical.
There's a demo... Really impressive. But this effectively works very well
for medial imagery, such as radiography, where the images have small
gradients and for which the traditional lossy compression technics loose too
much information in those tiny gradient areas, that preserves the smooth
transitions and precision of the color and light shades.
I would think at first that the compression technic is an adaptative system,
which really favors the compression of images with small contrasts such as
medical clichés (and in some measures the video images, but traditional
cameras used for cinema and even photography don't have the sufficient
precision and stability in their CCD cells to obtain stable and smooth
gradients: see the many unstable pixels which produce additional snowy noise
on those cameras; if you use lossless compression, you'll need to represent
and store this unstability, even if the human eye cannot see them; however
for medical imagery, the captors are much more stable and precise so the
power of this noise is very low, so this allows capturing the smoothest
gradients).
I am not sure it is adaptable to compress any type of image (for example
bitmaps, computer screenshots, cinema, etc... simply even when they are
captured with "high definition" cameras; but it may compress quite well the
computer generated raytraced images which are based on smooth mathematical
models, provided that these raytraces are not approximated by fast integer
functions with a too large quantification noise.)
Note also that medial imagery can obtain very high precision by using very
long pause time for the capture: the longer the pause time, the more the
captor will take captured images, that are then smoothed by a simple mean
function. This increases the precision of the shades, and reduces the power
of the captured noise (including the quantification noise), but the bad
thing is that this requires static (immobile) subjects. To reduce the
capture time, but keep a high precision, mediacal imagery requires a very
fast sensor capable of taking several hundreds of clichés per second,
instead of several dozens for cinema, or just a few for numeric photography.
To summarize: lossy compression is not a bad thing for classic photography
and video, because it can ignores the inherent noise caused by the capturing
source itself, and by numeric quantification (i.e. the 2D pixel size
quantification noise, and the per-pixel energy level quantification noise
implied by the necessarily limited number of bits to represent it).
And even for medical imagery, the quantification of the analog signal is
still required, all captors still have their own inherent noise (caused by
temperature, or by the effects of the variation of natural environmental
electromagnetic fields on the captor, or by nuclear desintegration,
unpredictable high energy particles like neutrinos, gravitation fields, or
simply the global "white noise" of the universe echoing the bigbang...); add
to this that mediacl imagery will concern *live* subjects that are not
completely static during the capture time. Is it still required to keep the
images with all this inherent noise? May be...
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