I am trying to classify thermal imagery using object based image analysis using Random Trees and Maximum likelihood classifiers. I was wondering if there are rules for how many training samples we should generate per class?
I'm looking for the same answer to you.
There is no such hard and fast rule, just make sure to start with equal training samples per class which are uniquely distributed across your AOI. You can increase then if you feel the output is not satisfactory.