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- W2766808328 abstract "Hyperspectral image processing benefits greatly from using spatial information. Markov field modeling is a well-known statistical model class for considering spatial relationships between sites of an image. Often, the model restricts to Hidden Markov Field, therefore cannot handle non-stationarities in the images. This paper presents a Triplet Markov Field model for hyperspectral image segmentation, allowing the joint retrieving of image classes and local orientations. Segmentation results on synthetic data validate the methods, and results on real astronomical data are presented." @default.
- W2766808328 created "2017-11-10" @default.
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- W2766808328 date "2016-08-01" @default.
- W2766808328 modified "2023-09-25" @default.
- W2766808328 title "Oriented Triplet Markov fields for hyperspectral image segmentation" @default.
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- W2766808328 doi "https://doi.org/10.1109/whispers.2016.8071755" @default.
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