Connected image processing with multivariate attributes: An unsupervised Markovian classification approach

@article{Perret2015ConnectedIP,
  title={Connected image processing with multivariate attributes: An unsupervised Markovian classification approach},
  author={Benjamin Perret and Christophe Collet},
  journal={Computer Vision and Image Understanding},
  year={2015},
  volume={133},
  pages={1-14}
}
This article presents a new approach for constructing connected operators for image processing and analysis. It relies on a hierarchical Markovian unsupervised algorithm in order to classify the nodes of the traditional Max-Tree. This approach enables to naturally handle multivariate attributes in a robust non-local way. The technique is demonstrated on several image analysis tasks: filtering, segmentation, and source detection, on astronomical and biomedical images. The obtained results show… CONTINUE READING