Path: utzoo!attcan!uunet!husc6!uwvax!oddjob!ncar!ames!elroy!mahendo!jplgodo!wlbr!etn-rad!jru
From: jru@etn-rad.UUCP (John Unekis)
Newsgroups: comp.graphics
Subject: Re: Fractal Compression
Keywords: Economic aspects, trade offs
Message-ID: <522@etn-rad.UUCP>
Date: 20 May 88 18:28:42 GMT
References: <686@thalia.rice.edu> <5546@cup.portal.com> <1947@tansei.cc.u-tokyo.JUNET>
Reply-To: jru@etn-rad.UUCP (John Unekis)
Organization: Eaton Inc. IMSD, Westlake Village, CA
Lines: 44

In article <1947@tansei.cc.u-tokyo.JUNET> b39756@tansei.cc.u-tokyo.JUNET (Martin J. Duerst) writes:
>In article <5546@cup.portal.com> doug-merritt@cup.portal.com writes:
>>Eric Salituro writes (wrt IFS image compression):
>>>I fail to see what the hoopla over fractal-based image compression is all
>>>about. In the last two weeks, I've read a couple of breathless articles
>>>proclaiming 1000 to 1 reduction but all I've seen as evidence are a couple
>>>of low-res pictures.  [...]
>>Compression ratios of *10,000* to 1 aren't all that unusual. The "close
.....
>    There are two aspects of exactness involved here. The first is how
>exactly the decoded image conforms to the abstract picture described by.....

I think I must be missing something here. I understand that it is possible to 
come up with representations for graphically generated images that are very 
compact. What I get frustrated with is the imprecision of terminology used 
when talking about image compression. The filled and shaded polygon images
used in cartoons and advertisements are easy to parameterize and can be stored
in forms that require very little data to be recorded. SO WHAT?

Suppose I give you an image from the real world. An example might be a 
digitized X-ray image. An exact representation of this image is absolutely 
critical since such problems as lumps of cancerous cells may initialy show up
as one or two dark pixels on the slide. No compression algorithm which might
either remove such pixels or allow them to be created by error is acceptable.
It is simply not good enough if the compression/decompression merely preserves
major details in recognizable form. Most hospitals will not allow compression
and decompression of such images unless it can be demonstrated that the 
reconstructed image when subtracted from the original yields ABSOLUTELY ZERO
different pixels. 

After years of looking at image compression I have not seen a compression 
technique which will exceed 10 to 1 on the average image (not one specially
selected to compress well) and still be completely non-destructive. My
impression is that these esoteric techniques like fractal compression only
produce these incredible compression ratios if you use images with large
areas with little detail in them , and you aren't terribly picky about 
accuracy in the reconstructed image. These kinds of techniques may be great
for sending childrens cartoons over telephone lines, but what use are they 
in real image processing? Am I wrong? Can somebody refer me to literature
that gives a compression technique for real images that will produce better
than 10 to 1 with not even 1 pixel difference in the reconstructed image?
I seriously doubt it.

				voder!wlbr!etn-rad!jru