Hi St�fan
If you had a mask for an individual superpixel, and indices into your array, x, y, z, you can imagine finding the coordinates of all pixels under that mask with
x[mask], y[mask], z[mask]
The mask you typically recover from a label image, so, e.g., mask = (labels == 3).
Thanks.
Now, the trickier problem is figuring out where, relative to other super-pixels, this one is located. For that, it may be better to represent the image as a graph, where each node represents a super-pixel, and edges represent links to other super-pixels (in fact, I assumed/hoped there is some python based graph library that was numpy friendly.
this is something we should implement in scikit-image to make handling labels easier).
Would you be interested in collaborating on such a feature? Sure. I am still feeling my way, but am willing to contribute what every way I can.
Regards, Michael. --