Plugin procedure in segmentation and application to hyperspectral image segmentation. (English) Zbl 1329.62280

Girard, Robin

Electron. J. Stat. 4, 655-676 (2010).

Summary: 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 E. D. Kolaczyk et al. [J. Am. Stat. Assoc. 100, No. 472, 1358–1369 (2005; Zbl 1117.62371)].

MSC:

62H30	Classification and discrimination; cluster analysis (statistical aspects)
62H35	Image analysis in multivariate analysis
62M40	Random fields; image analysis

Keywords:

segmentation; mixture model; penalized maximum likelihood estimation; dimensionality reduction

Citations:

Zbl 1117.62371

References:

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