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Immersive Interactive SAR Image Representation Using Non-negative Matrix Factorization

Babaee, Mohammadreza and Yu, Xuejie and Rigoll, Gerhard and Datcu, Mihai (2016) Immersive Interactive SAR Image Representation Using Non-negative Matrix Factorization. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9 (7), pp. 2844-2853. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2015.2511449 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/document/7426732/


Earth observation (EO) image clustering is a challenging problem in data mining, where each image is represented by a high-dimensional feature vector. However, the feature vectors might not be appropriate to express the semantic content of images, which eventually lead to poor results in clustering and classification. To tackle this problem, we propose an interactive approach to generate compact and informative features from images content. To this end, we utilize a 3-D interactive application to support user-image interactions. These interactions are used in the context of two novel nonnegative matrix factorization (NMF) algorithms to generate new features. We assess the quality of new features by applying k-means clustering to the generated features and compare the obtained clustering results with those achieved by original features. We perform experiments on a synthetic aperture radar (SAR) image dataset represented by different state-of-the-art features and demonstrate the effectiveness of the proposed method. Moreover, we propose a divide-and-conquer approach to cluster a massive amount of images using a small subset of interactions.

Item URL in elib:https://elib.dlr.de/105903/
Document Type:Article
Title:Immersive Interactive SAR Image Representation Using Non-negative Matrix Factorization
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Babaee, MohammadrezaTechnical University Munich, GermanyUNSPECIFIED
Yu, XuejieTechnical University Munich, GermanyUNSPECIFIED
Rigoll, GerhardTechnical University Munich, GermanyUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:July 2016
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1109/JSTARS.2015.2511449
Page Range:pp. 2844-2853
Du, QuianMississippi State University
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:Nonnegative matrix factorization (NMF), clustering, feature learning, immersive interactive systems
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 > Photogrammetry and Image Analysis
Deposited By: Schwarz, Gottfried
Deposited On:05 Sep 2016 10:43
Last Modified:31 Jul 2019 20:03

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