3.4 Classification

  3.4.1 Pixel based classification
   Statistics estimation
   Building the training data set
   Performing the learning scheme
   Using the classification model
   Validating the classification model
   Fancy classification results
   Example
  3.4.2 Fusion of classification maps
   Majority voting for the fusion of classifications
   Dempster Shafer framework for the fusion of classifications
   Recommendations to properly use the fusion of classification maps
  3.4.3 Majority voting based classification map regularization
   Majority voting for the classification map regularization
   Handling ambiguity and not classified pixels in the majority voting based regularization
   Recommendations to properly use the majority voting based regularization
   Example
  3.4.4 Regression
   Input datasets
   Statistics estimation
   Training
   Prediction
  3.4.5 Samples selection