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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Hyperspectral Data Classification Using Extended Extinction Profiles

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Author(s):
Ghamisi, Pedram ; Souza, Roberto ; Benediktsson, Jon Atli ; Rittner, Leticia ; Lotufo, Roberto ; Zhu, Xiao Xiang
Total Authors: 6
Document type: Journal article
Source: IEEE Geoscience and Remote Sensing Letters; v. 13, n. 11, p. 1641-1645, NOV 2016.
Web of Science Citations: 27
Abstract

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. (AU)

FAPESP's process: 15/12127-0 - Max-trees applied to medical images segmentation
Grantee:Roberto Medeiros de Souza
Support type: Scholarships abroad - Research Internship - Doctorate
FAPESP's process: 13/23514-0 - Max-Tree: theory, algorithms and applications
Grantee:Roberto Medeiros de Souza
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology
Grantee:Fernando Cendes
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC