Katartzis, A., Vanhamel, I., & Sahli, H. (2005). A Hierarchical Markovian Model for Multiscale Region-based Classification of Vector-Valued Images. IEEE Transactions on Geoscience and Remote Sensing, 43(3), 548-558. http://ieeexplore.ieee.org/search/freesrchabstract.jsp?tp=&arnumber=1396327&queryText%3DA+Hierarchical+Markovian+Model+for+Multiscale+Region-based+Classification+of+Vector-Valued+Images%26openedRefinements%3D*%26searchField%3DSearch+All

@article{6a1d62cf63804992808d3204758e6b98,
title = "A Hierarchical Markovian Model for Multiscale Region-based Classification of Vector-Valued Images",
abstract = "We propose a new classification method for vector-valued images, based on: 1) a causal Markovian model, defined on the hierarchy of a multiscale region adjacency tree (MRAT), and 2) a set of nonparametric dissimilarity measures that express the data likelihoods. The image classification is treated as a hierarchical labeling of the MRAT, using a finite set of interpretation labels (e.g., land cover classes). This is accomplished via a noniterative estimation of the modes of posterior marginals (MPM), inspired from existing approaches for Bayesian inference on the quadtree. The paper describes the main principles of our method and illustrates classification results on a set of artificial and remote sensing images, together with qualitative and quantitative comparisons with a variety of pixel-based techniques that follow the Bayesian-Markovian framework either on hierarchical structures or the original image lattice.",
author = "Antonis Katartzis and Iris Vanhamel and Hichem Sahli",
note = "IEEE Transactions on Geoscience and Remote Sensing (Special Issue on Advances in Techniques for Analysis of Remotely Sensed Data), Vol. 43, Nr. 3, pp. 548-558.",
year = "2005",
language = "English",
volume = "43",
pages = "548--558",
journal = "IEEE Transactions on Geoscience and Remote Sensing",
issn = "0196-2892",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",
}