Performance evaluation of road and building classifiers on VHR images

A method is proposed for building and road detection on VHR multispectral aerial images of dense urban areas. Spatial and spectral features of segmented areas are classified using a 3-class SVM integrating some a priori and contextual information to handle unclassified patterns and conflicts. Geometrical object features and additional information improve the classification accuracy in the difficult case where many building roofs are grey like the roads and have similar geometry. Also, road network regularization is suggested to improve the classification accuracy.