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Hyperspectral Data Classification Using Extended Extinction Profiles

Ghamisi, Pedram and Souza, Roberto and Benediktsson, Jon Atli and Rittner, Leticia and Lotufo, Roberto and Zhu, Xiao Xiang (2016) Hyperspectral Data Classification Using Extended Extinction Profiles. IEEE Geoscience and Remote Sensing Letters, 13 (11), pp. 1641-1645. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/LGRS.2016.2600244 ISSN 1545-598X

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Official URL: http://ieeexplore.ieee.org/document/7551242/

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.

Item URL in elib:https://elib.dlr.de/106356/
Document Type:Article
Title:Hyperspectral Data Classification Using Extended Extinction Profiles
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ghamisi, PedramDLR-IMF/TUM-LMFUNSPECIFIED
Souza, RobertoSchool of Electrical and Computer Engineering - UNICAMPUNSPECIFIED
Benediktsson, Jon AtliFaculty of Electrical and Computer Engineering, University of Iceland, 107 Reykjavik, IcelandUNSPECIFIED
Rittner, LeticiaSchool of Electrical and Computer Engineering - UNICAMPUNSPECIFIED
Lotufo, RobertoSchool of Electrical and Computer Engineering - UNICAMP, BrazilUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:August 2016
Journal or Publication Title:IEEE Geoscience and Remote Sensing Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:13
DOI :10.1109/LGRS.2016.2600244
Page Range:pp. 1641-1645
Editors:
EditorsEmail
Frery, Alejandro C.acfrery@gmail.com
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1545-598X
Status:Published
Keywords:Extended multiextinction profile (EMEP), hyperspectral data classification, random forests (RFs), support vector machines (SVMs).
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Ghamisi, Pedram
Deposited On:19 Oct 2016 10:00
Last Modified:31 Jul 2019 20:03

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