Select training samples — homogeneous AOIs per class.
Generate & evaluate statistical signatures — mean, std, covariance per band.
Class assignment via a decision rule (Min Distance, Max Likelihood, etc.).

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Train → Stats → Classify. You TEACH the computer with samples, it LEARNS signatures (mean + covariance), then APPLIES a decision rule to every pixel.

classification/supervised-training