Incorporating mixed pixels in the training, allocation and testing stages of supervised classifications

Abstract

Conventional supervised classifiers cannot accommodate mixed pixels directly but may be modified to do so throughout the classification process. Here mixed pixels are included in all three stages of maximum likelihood and neural network classifications. The results show that by accommodating for mixed pixels in the classification, more accurate, appropriate and useful outputs may be derived.