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Quantitative Evaluation of the Feature Space Transformation Methods Used for Applications of Visual Semantic Clustering of EO Images

Griparis, Andreea and Faur, Daniela and Datcu, Mihai (2017) Quantitative Evaluation of the Feature Space Transformation Methods Used for Applications of Visual Semantic Clustering of EO Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (6), pp. 2902-2909. IEEE - Institute of Electrical and Electronics Engineers. ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7938605

Abstract

Data visualization guides the process of indexing and retrieval, strengthening the link between low-level image Features and high-level human understanding of image content. In this regard, we have described the semantic content of a multidimensional dataset using its descriptors to derive high-dimensional feature spaces. The dimensionality of these spaces is further reduced to three in order to provide a three-dimensional (3-D) representation of the dataset items. Our main challenge was to identify the Transformation that projects the high-dimensional feature set into a 3-D space preserving its semantic content. To overcome this issue, we have compared the efficiency of 11 feature space transformations: one feature selection algorithm and ten dimensionality reduction methods. As long as the dataset properties, during mapping, may differ depending on the chosen algorithm, the performance comparison of multiple algorithms is a difficult task. Therefore, three quantitative measures have been used: Trustworthiness, Continuity, and QNX - the number of points preserved in data neighborhoods over projection. Themapping algorithms have been applied to three remote sensing datasets achieved from different sensors: LANDSAT 7 ETM+ andWorldView-3.

Item URL in elib:https://elib.dlr.de/113877/
Document Type:Article
Title:Quantitative Evaluation of the Feature Space Transformation Methods Used for Applications of Visual Semantic Clustering of EO Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Griparis, Andreeauniversity politehnica of bucharest, romaniaUNSPECIFIED
Faur, Danielauniversity politehnica of bucharest, bucharest, romaniaUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:June 2017
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:10
Page Range:pp. 2902-2909
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Dimensionality, evaluation, exploration, multidimensional data, reduction, visualization
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: Zielske, Mandy
Deposited On:05 Sep 2017 18:27
Last Modified:08 Mar 2018 18:32

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