Hi Josh,
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 (including myself!).
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 https://github.com/emmanuelle/scikits.image/tree/fix_random_walker, maybe you can include these changes when you contribute your changes?
Cheers, Emmanuelle
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. �I really liked the existing algorithm, so I just extended it rather than write one from scratch for my own purposes. �The overhead is minimal; multispectral processing is triggered if data is passed as an iterable of arrays rather than just an array. � This amounts to combining image gradients as sqrt(sum-of-squares) and dividing by sqrt(#channels). �For obvious reasons, the several channels must be pre-processed to have data on similar ranges by whitening or a similar method. �Not usually a problem for RGB, but in medical imaging this rears its head. Would this be of interest to the community? �I'd be happy to contribute the changes if there is interest.