Artículos de revistas
Hyperspectral Data Classification Using Extended Extinction Profiles
Registro en:
Ieee Geoscience And Remote Sensing Letters. Ieee-inst Electrical Electronics Engineers Inc, v. 13, p. 1641 - 1645, 2016.
1545-598X
1558-0571
WOS:000386255600011
10.1109/LGRS.2016.2600244
Autor
Ghamisi
Pedram; Souza
Roberto; Benediktsson
Jon Atli; Rittner
Leticia; Lotufo
Roberto; Zhu
Xiao Xiang
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) This letter proposes a new approach for the spectral-spatial classification of hyperspectral images, which is based on a novel extrema-oriented connected filtering technique, entitled as extended extinction profiles. The proposed approach progressively simplifies the first informative features extracted from hyperspectral data considering different attributes. Then, the classification approach is applied on two well-known hyperspectral data sets, i.e., Pavia University and Indian Pines, and compared with one of the most powerful filtering approaches in the literature, i.e., extended attribute profiles. Results indicate that the proposed approach is able to efficiently extract spatial information for the classification of hyperspectral images automatically and swiftly. In addition, an array-based node-oriented max-tree representation was carried out to efficiently implement the proposed approach. 13 11 1641 1645 Alexander von Humboldt Fellowship for Postdoctoral Researchers Helmholtz Young Investigators Group "SiPEO" - Fundacao de Amparo a Pesquisa do Estado de Sao Paulo [VH-NG-1018, 2013/23514-0, 2015/12127-0, 2013/07559-3] CNPq [311228/2014-3] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)