This is an example of a patent I think the free software community
could beat.
(1) Let's imagine that we had some sort of non-linear convolution which
trimmed bits off the image (probably need a couple stages, so it's going
to take a lot of work to design it). So, design a basic framework which
has roughly the right kind of algorithmic properties, and characterize
its parameter space.
(2) Build a big database of before/after compressed images, making sure
that the "after" images are high quality. [Note that you can have more
than one good "after" image.] Even better than a database would be
"too slow but damned good" algorithm that we want to emulate, but I
don't know that there is one.
(3) Run a search in the parameter space of your convolution framework
for a decent transform. Tune it by hand if you can, but just throw
massive parallelism at it (probably make it a genetic algorithm if
you can come up with some kind of "this is good/this is bad" metric)
to pick out a good compression scheme. [Example of how to parallelize:
farm out image pairs to machines, then each machine a stream of parameters
and have them pick the "best n".]
(4) Once you've gotten as far as you can with this system, start getting
real people to look at before/after sets and pick out what they think
is best, and use this as a [Use porn images and you'll have lots of
volunteers.]
Convolution is old hat, non-linear algorithms are old hat, searching and
genetic algorithms are old hat (so are neural net training algorithms,
which I didn't mention but which might be useful here), and polling
people to find out their preferences is old hat. And at no time are
we using a "perceptual model" to design the transform -- we're using
real perception.
This is just a sketch of an idea, and there's some serious room for
improvement, but the underlying concept should work for any lossy
compression algorithm.
-- Raul- To unsubscribe from this list: send the line "unsubscribe linux-kernel" in the body of a message to majordomo@vger.rutgers.edu Please read the FAQ at http://www.tux.org/lkml/