Abstract
In this work we give our contribution to the problem of segmentation with plug-in procedures. We propose general sufficient conditions under which plug in procedure are efficient. We also give an algorithm that satisfy these conditions. We apply this algorithm to hyperspectral images segmentation. Hyperspectral images are images that have both spatial and spectral coherence with thousands of spectral bands on each pixel. In the proposed procedure we combine a reduction dimension technique and a spatial regularization technique. This regularization is based on the mixlet modeling of Kolaczyck et al. [10].
Citation
Robin Girard. "Plugin procedure in segmentation and application to hyperspectral image segmentation." Electron. J. Statist. 4 655 - 676, 2010. https://doi.org/10.1214/10-EJS567
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