NDLI: Semi-supervised discriminative random field for hyperspectral image classification

Content Provider	IEEE Xplore Digital Library
Author	Jun Li Bioucas-Dias, J.M. Plaza, A.
Copyright Year	2012
Description	Author affiliation: Dept. of Technol. of Comput. & Commun., Univ. of Extremadura, Caceres, Spain (Jun Li; Plaza, A.) \|\| Inst. de Telecomun., Tech. Univ. of Lisbon, Lisbon, Portugal (Bioucas-Dias, J.M.)
Abstract	Remotely sensed hyperspectral imaging allows for the detailed analysis of the surface of the Earth using advanced imaging instruments which can produce high-dimensional images with hundreds of spectral bands. Supervised hyperspectral image classification is a difficult task due to the unbalance between the high dimensionality of the data and the limited availability of labeled training samples in real analysis scenarios. While the collection of labeled samples is generally difficult, expensive and time-consuming, unlabeled samples can be generated in a much easier way. This observation has fostered the idea of adopting semi-supervised learning (SSL) techniques in hyperspectral image classification. The main assumption of such techniques is that the new (unlabeled) training samples can be obtained from a (limited) set of available labeled samples without significant effort/cost. In this work, we propose a new semi-supervised discriminative random field (SSDRF) technique for spectral-spatial hyperspectral image classification. The proposed approach is validated using a hyperspectral dataset collected using NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Indian Pines region. The obtained results indicate that, by automatically generating unlabeled information, the proposed SSDRF algorithm exhibits very good performance in terms of accuracies in comparison with supervised algorithms. In terms of computational cost, the proposed SSDRF algorithm self learns the classifier with the same complexity as the supervised algorithm, and converges very efficiently.
Starting Page	1
Ending Page	4
File Size	655479
Page Count	4
File Format	PDF
e-ISBN	9781479934065
DOI	10.1109/WHISPERS.2012.6874224
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Loopy belief propagation (LBP) Spectralspatial analysis Computational modeling Semi-supervised learning Abstracts Probabilistic logic Discriminative random field Indexes Hyperspectral image classification
Content Type	Text
Resource Type	Article

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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