Making algorithms at least 3D, preferably nD

[Johannes Schönberger]

> Volumetric image processing is definitely within scope of the scikit.
> The reason that most of the implementations up to this point were 2-D
> is simply a lack of time and hands.  Luckily, that seems to be
> changing, so we may very well have the luxury of tackling this problem
> head-on.

I also think that the majority of use cases is based on 2-D data (plus channel data) and volumentric data is a specific and rare use case.

I'm also dealing with lots of nD data (3-D, 4-D,…), nevertheless they are mostly still 2-D data. E.g.
 - SAR stacks (NxMxD)
 - Covariance matrix images (NxMxDxD)
 - Hyperspectral remote sensing images (NxMxD)
 - Tomographic SAR (NxMxJxD)
 - etc.
where D is often > 200.