Hong, Danfeng and Yokoya, Naoto and Zhu, Xiao Xiang (2016) Local Manifold Learning with Robust Neighbors Selection for Hyperspectral Dimensionality Reduction. In: Proceedings of IGARSS 2016, pp. 40-43. IEEE Xplore. IGARSS 2016, 10-15 July 2016, Beijing, China. doi: 10.1109/IGARSS.2016.7729001. ISSN 2153-7003 (E).
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Official URL: http://ieeexplore.ieee.org/document/7729001/
Abstract
Manifold learning has been successfully applied to hyperspectral dimensionality reduction to embed nonlinear and nonconvex manifolds in the data. However, dimensionality reduction by manifold learning is sensitive to non-uniform data distribution and the selection of neighbors. To address the two issues to some extents, in this work a new manifold framework based on locality linear embedding (LLE), namely local normalization and local feature selection (LNLFS), is proposed. Classification is explored as a potential application to validate the proposed algorithm. Classification accuracy using data obtained using different dimensionality reduction methods is evaluated and compared, while applying two kinds of strategies for selecting the training and test samples: random sampling and region-based sampling. Experimental results show the classification accuracy obtained with LNLFS is superior to state-of-the-art dimensionality reduction methods.
Item URL in elib: | https://elib.dlr.de/109187/ | ||||||||||||
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Document Type: | Conference or Workshop Item (Lecture) | ||||||||||||
Title: | Local Manifold Learning with Robust Neighbors Selection for Hyperspectral Dimensionality Reduction | ||||||||||||
Authors: |
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Date: | January 2016 | ||||||||||||
Journal or Publication Title: | Proceedings of IGARSS 2016 | ||||||||||||
Refereed publication: | No | ||||||||||||
Open Access: | Yes | ||||||||||||
Gold Open Access: | No | ||||||||||||
In SCOPUS: | No | ||||||||||||
In ISI Web of Science: | No | ||||||||||||
DOI : | 10.1109/IGARSS.2016.7729001 | ||||||||||||
Page Range: | pp. 40-43 | ||||||||||||
Editors: |
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Publisher: | IEEE Xplore | ||||||||||||
ISSN: | 2153-7003 (E) | ||||||||||||
Status: | Published | ||||||||||||
Keywords: | hyperspectral image, dimensionality reduction, manifold learning, local normalization, local feature selection, non-uniform data distribution | ||||||||||||
Event Title: | IGARSS 2016 | ||||||||||||
Event Location: | Beijing, China | ||||||||||||
Event Type: | international Conference | ||||||||||||
Event Dates: | 10-15 July 2016 | ||||||||||||
Organizer: | GRSS | ||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||
HGF - Program: | Space | ||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||
DLR - Research theme (Project): | R - Vorhaben hochauflösende Fernerkundungsverfahren (old) | ||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||
Institutes and Institutions: | Remote Sensing Technology Institute > SAR Signal Processing | ||||||||||||
Deposited By: | Hong, Danfeng | ||||||||||||
Deposited On: | 08 Dec 2016 08:26 | ||||||||||||
Last Modified: | 31 Jul 2019 20:06 |
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