Hyperspectral Data Classification Using Extended Extinction Profiles

Author(s)

Ghamisi, Pedram ; Souza, Roberto ; Benediktsson, Jon Atli ; Rittner, Leticia ; Lotufo, Roberto ; Zhu, Xiao Xiang

• 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