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**Maximum Likelihood Classification (MLC)** assumes each class's pixel values follow a **multivariate Gaussian** distribution. For each unknown pixel, it computes the probability of membership in every class (from the class mean and covariance matrix) and assigns the pixel to the class with the **highest probability**. - **Strength:** statistically principled; handles correlated bands well. - **Weakness:** requires enough training samples to estimate covariance reliably; struggles when classes aren't Gaussian.

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