I'd be happy to include your suggested changes, if it's simpler to go that route than have two separate pull requests. I don't want to step on any toes regarding attribution, though.
extending the random walker algorithm to multichannel images sounds like
a very nice idea, and I'm sure that it would be useful for other people
In fact, I had started working on some improvements of the random walker
code but didn't go as far as proposing the pull request. I have a branch
for that on
scikits.image/tree/fix_random_, maybe walker
you can include these changes when you contribute your changes?
On Mon, Aug 20, 2012 at 10:03:53AM -0700, Josh Warner wrote:
> I have modified the existing random walker algorithm into a fully
> backwards-compatible version which allows inclusion of multispectral data,
> e.g. RGBA channels or different (registered) image modalities. ï¿½I really
> liked the existing algorithm, so I just extended it rather than write one
> from scratch for my own purposes. ï¿½The overhead is minimal; multispectral
> processing is triggered if data is passed as an iterable of arrays rather
> than just an array. ï¿½
> This amounts to combining image gradients as sqrt(sum-of-squares) and
> dividing by sqrt(#channels). ï¿½For obvious reasons, the several channels
> must be pre-processed to have data on similar ranges by whitening or a
> similar method. ï¿½Not usually a problem for RGB, but in medical imaging
> this rears its head.
> Would this be of interest to the community? ï¿½I'd be happy to contribute
> the changes if there is interest.