dolfin team mailing list archive

[A Navaei <axnavaei@xxxxxxxxxxxxxx>]

2009/2/24 Harish Narayanan <harish.mlists@xxxxxxxxx>:
> A Navaei wrote:
>> Finally after all those long discussions on the best way of
>> architecturing variational image processing problems based on dolfin,
>> a minimal demo showing how to solve a classical motion estimation PDE
>> is available now -- thanks for all the support. Detailed explanation
>> is given here:
>>
>> http://code.google.com/p/debiosee/wiki/DemosOptiocFlowHornSchunck
>
> Looks interesting. Are there plans to (or is it straightforward to)
> extend this to other functionals to process the image in other ways?
> (e.g. Edge detection and selective smoothening/sharpening.)

Both of the good points that you mentioned are part of the main goals
of Debiosee. The project was created with the idea of implementing a
comprehensive set of variational algorithms with applications in image
processing. Anyone interested in such contribution is welcome to join.

Selecting fenics as the variational engine and itk as the image
processing library, provides a rich combination of tools making it
very likely that you would find the necessary requirement available if
you want to solve a new problem. Moreover, since both libraries come
with excellent rapid prototyping features, eg variational forms in
dolfin or automated template wrapping in itk, developing will be fast
and demands less programming skills. Variational image processing is a
young since, paper [1] is a good introduction to some applications.


-Ali


[1] http://www.math.ucla.edu/~lvese/PAPERS/fea-shen-03.pdf

>
> Harish
>