Re: [Gimp-developer] Looking for applications for this math idea

Denoising is another obvious application. You could perhaps do your
decomposition at various points over the image surface and see if you
can find some noise function that's present everywhere and that
therefore comes from the sensor rather than the object.

Again, there is a huge literature and it's a difficult problem.

On 28 February 2015 at 13:54, Bill Skaggs <weskaggs gmail com> wrote:
Decomposing a distribution into Gaussians is the essence of unblurring.  A
good algorithm for doing that would of course be very useful, but there is
an enormous literature on the topic, and the most important fact about it
is that it is mathematically ill-posed.  In other words, unless you add
extra constraints, tiny changes in the source distribution result in very
large changes in the output.  (In image-processing terms, transforms of
that type tend to create large artifacts.) Unless the new method has some
way of handling that problem, it probably isn't going to be useful.

On Fri, Feb 27, 2015 at 3:56 PM, Ben Thurston <
benpaulthurston gmail com


I developed this type of function that I feel is sort of like the
statistical analogue of the Fourrier series, it breaks a distribution
into simple normal distribution components as the Fourrier series
breaks a
wave into simple sine wave components. I thought maybe there could be
application for it in image processing but I don't know enough about
processing to figure out how it would apply... Anyone have any ideas?

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