Supervised re-segmentation for very high-resolution satellite images
Julien Michel, Manuel Grizonnet, Olivier Canévet · 2012
In this paper, we proposed a supervised methodology to enhance an existing segmentation in which we assume that objects of interest are mainly fragmented. We used a SVM classifier to classify edges from the adjacency graph of the initial segmentation, described with features on the pair of segments and their relationship. Pairs of segments are then merged sequentially according to the classifier decision. We also proposed three methods for efficient supervision by the end user.