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For anyone looking for an answer or hints on this or specifically about being able to cluster multiple images easily, the way i found was using parts of the Bag of Words classes in the c++ api for opencv.
BOWTrainer::add
specifically will allow you to push back as multiple Mat images easily and and then generate a set of cluster centers using:
BOWTrainer::cluster
Definitely better than messing around trying to cluster them with the traditional kmeans function.
I haven't yet found a good solution to matching the cluster centres with the the generated vocabulary yet, as the other BOW opencv classes as far as i can tell wont work when using filterbanks. So i'll update it when i find something, otherwise you can check my current implementation on github: https://github.com/albertJ32/multiChannel_Kmeans_c
