NDLI: Dimensionality Reduction of Hyperspectral Data via Spectral Feature Extraction

Content Provider	IEEE Xplore Digital Library
Author	Mojaradi, B. Abrishami-Moghaddam, H. Zoej, M.J.V. Duin, R.P.W.
Copyright Year	1980
Abstract	This paper proposes an innovative spectral feature extraction (SFE) method called prototype space (PS) feature extraction (PSFE) based only on class spectra. The main novelties of the proposed SFE lie in the following: representing channels in a new space called PS, where they are characterized in terms of reflection properties of classes; and proposing uncertainty, angle, and distance measures to distinguish highly correlated and informative channels. Having clustered the channels by Fuzzy C-Means (FCM) in PS, highly correlated and isolated channels are separated by an uncertainty measure. Consequently, PSFE is built by a linear combination of spectra weighted by class membership values of channels that fall in each cluster. Furthermore, we will enrich PSFE with informative channels which are outlier channels identified through their angle and distance with respect to diagonal and cluster centers in PS. In contrast to the previous SFE methods, PSFE substitutes the search strategies with FCM clustering to find relevant channels. Moreover, instead of optimizing separability criteria, the accuracy of classification over a subset of training data is used to decide which disjoint optical region yields maximum accuracy. According to how class spectra are obtained, PSFE incorporates four approaches: knowledge based, supervised, semisupervised, and unsupervised. The latter three PSFE approaches are assessed in two main cases including with and without informative channels and compared with the conventional feature extraction methods. Experimental results demonstrated higher overall accuracy of PSFE compared to its conventional counterparts with limited sample sizes.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	2091
Ending Page	2105
Page Count	15
File Size	2063075
File Format	PDF
ISSN	01962892
Volume Number	47
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral imaging Feature extraction Hyperspectral sensors Training data Space technology Laboratories Geodesy Data mining Java Prototypes spectral feature Feature extraction (FE) hyperspectral images remote-sensing image classification
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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