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Feature space dimensionality reduction for the optimization of visualization methods

Griparis, Andreea and Faur, Daniela and Datcu, Mihai (2015) Feature space dimensionality reduction for the optimization of visualization methods. In: Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International, pp. 1120-1123. IEEE Xplore. IGARSS 2015, 26-31 Jul 2015, Milan, Italy. DOI: 10.1109/IGARSS.2015.7325967

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7325967


Visual data mining methods are of great importance in exploratory data analysis having a high potential for mining large databases. As the data feature space is generally n-dimensional, visual data mining relies on dimensionality reduction techniques. This is the case for image feature spaces which can be visualized by giving each data point a location in a three dimensional space. This paper aims to present a comparative study of several dimensionality reduction methods considering as input image feature spaces, in order to detemine an optimal visualization method to illustrate the separation of the classes. At the beginning, to check the performance of the envisaged method, an artificial dataset consisting of random vectors describing six, 20-dimensional Gaussian distributions with spaced means and low variances was generated. Further, two real images datasets are used to evaluate the contributions of dimensionality reduction algorithms related to data visualization. The analysis focuses on the PCA, LDA and t-SNE dimensionality reduction techniques. Our tests are performed on images for which the computed features include the color histogram and Weber descriptors.

Item URL in elib:https://elib.dlr.de/100672/
Document Type:Conference or Workshop Item (Poster)
Title:Feature space dimensionality reduction for the optimization of visualization methods
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:July 2015
Journal or Publication Title:Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2015.7325967
Page Range:pp. 1120-1123
Publisher:IEEE Xplore
Keywords:classification, dimensionality reduction, features vectors, visualization
Event Title:IGARSS 2015
Event Location:Milan, Italy
Event Type:international Conference
Event Dates:26-31 Jul 2015
Organizer:IEEE Geoscience and Remote Sensing Society
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 On:11 Dec 2015 17:10
Last Modified:10 May 2016 23:37

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