NDLI: A decision fusion approach for clustering of hyperspectral data using spectral unmixing methods

Content Provider	IEEE Xplore Digital Library
Author	Gholizadeh, H. Zoej, M.J.V. Mojaradi, B.
Copyright Year	2012
Description	Author affiliation: School of Civil Engineering, Iran University of Science and Technology, Tehran, P.O. Box 16765-163 (Mojaradi, B.) \|\| Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Vali-Asr St., Mirdamad Crossing, Tehran, P.O. Box: 15875-4416 (Gholizadeh, H.; Zoej, M.J.V.)
Abstract	This paper aims at a decision fusion approach for combining three spectral unmixing methods to cluster hyperspectral data. Unlike standard image clustering techniques, analyzing hyperspectral data on a pure pixel basis may not be a true assumption. Meanwhile, multiple classifier systems often show better performance than each of the constituent classifiers. This is due to the fact that each classifier makes errors on different regions of the input space. With these facts in mind, this paper distills these two approaches into a single approach and exploits the advantages of both spectral unmixing algorithms and decision fusion methods. In this paper, three unmixing methods namely, Fully Constrained Least Squares (FCLS), Nonnegatively Constrained Least Squares (NCLS) and Sum-to-one Constrained Least Squares (SCLS) are employed as the ensemble classifiers and their results are combined at two different fusion levels: the abstract level and the measurement level. Experimental results on a real-world hyperspectral data proved that the proposed approach shows better clustering results compared to those of K-Means and Fuzzy c-Means in terms of the Adjusted Random Index (ARI) measure.
Starting Page	1
Ending Page	7
File Size	986492
Page Count	7
File Format	PDF
ISBN	9781457705564
ISSN	1095323X
e-ISBN	9781457705571
DOI	10.1109/AERO.2012.6187197
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral imaging Clustering algorithms Clustering methods Time measurement Educational institutions Algorithm design and analysis
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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