Minimum Distance (to means) classification assigns each pixel to the class whose mean vector is closest in feature space — typically Euclidean distance across all bands.

• Strength: fast, works with small training sets.
• Weakness: ignores class shape and variance; poor when classes have very different spreads or are correlated in band space.