In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation. The method exploits the mean-shift clustering algorithm that takes as input a preliminary hyperspectral superpixels segmentation together with the spectral pixel information. The proposed method does not require the number of segmentation classes as input parameter, and it does not exploit any a-priori knowledge about the type of land-cover or land-use to be segmented (e.g. water, vegetation, building etc.). Experiments on Salinas, SalinasA, Pavia Center and Pavia University datasets are carried out. Performance are measured in terms of normalized mutual information, adjusted Rand index and F1-score. Results demonstrate the validity of the proposed method in comparison with the state of the art.

Barbato, M., Napoletano, P., Piccoli, F., Schettini, R. (2022). Unsupervised segmentation of hyperspectral remote sensing images with superpixels. REMOTE SENSING APPLICATIONS, 28 [10.1016/j.rsase.2022.100823].

Unsupervised segmentation of hyperspectral remote sensing images with superpixels

Barbato M. P.
;
Napoletano P.;Piccoli F.;Schettini R.
2022

Abstract

In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation. The method exploits the mean-shift clustering algorithm that takes as input a preliminary hyperspectral superpixels segmentation together with the spectral pixel information. The proposed method does not require the number of segmentation classes as input parameter, and it does not exploit any a-priori knowledge about the type of land-cover or land-use to be segmented (e.g. water, vegetation, building etc.). Experiments on Salinas, SalinasA, Pavia Center and Pavia University datasets are carried out. Performance are measured in terms of normalized mutual information, adjusted Rand index and F1-score. Results demonstrate the validity of the proposed method in comparison with the state of the art.
Articolo in rivista - Articolo scientifico
Hyperspectral images; Remote sensing; Superpixel segmentation; Unsupervised segmentation;
English
Barbato, M., Napoletano, P., Piccoli, F., Schettini, R. (2022). Unsupervised segmentation of hyperspectral remote sensing images with superpixels. REMOTE SENSING APPLICATIONS, 28 [10.1016/j.rsase.2022.100823].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/400805
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