[IP3-4-2-2] Maximum likelihood

Maximum likelihood classification uses the training data for estimating means and variances of the classes, which are then used to estimate the probabilities. This method considers not only the mean, or average, values in assigning classification but also the variability of brightness values in each class.

External resources

• Campbell, J.B., & Wynne, R.H. (2011). Introduction to remote sensing. Guilford Press, New York-London

Learning outcomes

• 1176 - Explain why multimodal distributions in training samples should be avoided when using the maximum likelihood classifier

  Explain why multimodal distributions in training samples should be avoided when using the maximum likelihood classifier

Self assessment

Outgoing relations

• [IP3-4-2-2] Maximum likelihood subclassof [IP3-4] Image classification