Detection of Land-Cover Transitions in Multitemporal Remote Sensing Images With Active-Learning-Based Compound Classification

@article{Demir2012DetectionOL,
  title={Detection of Land-Cover Transitions in Multitemporal Remote Sensing Images With Active-Learning-Based Compound Classification},
  author={Beg{\"u}m Demir and Francesca Bovolo and Lorenzo Bruzzone},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2012},
  volume={50},
  pages={1930-1941}
}
This paper presents a novel iterative active learning (AL) technique aimed at defining effective multitemporal training sets to be used for the supervised detection of land-cover transitions in a pair of remote sensing images acquired on the same area at different times. The proposed AL technique is developed in the framework of the Bayes' rule for compound classification. At each iteration, it selects the pair of spatially aligned unlabeled pixels in the two images that are classified with the… CONTINUE READING
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