NDLI: Measuring the Effectiveness of Various Features for Thematic Information Extraction From Very High Resolution Remote Sensing Imagery

Content Provider	IEEE Xplore Digital Library
Author	Xi Chen Tao Fang Hong Huo Deren Li
Copyright Year	1980
Abstract	Generally, some object-based features are more relevant to a thematic class than other features. These strongly relevant features, termed as class-specific features, would significantly contribute to thematic information extraction for very high resolution (VHR) images. However, many existing feature selection methods have been designed to select a good feature subset for all classes, rather than an independent feature subset for the thematic class. The latter might better meet the requirement of thematic information extraction than the former. In addition, the lack of quantitative evaluation of the contribution of the selected features to thematic classes also weakens our understandability of these features. To address the problems, class-specific feature selection methods are developed to measure the effectiveness of features for extracting thematic information from VHR images. First, the one-versus-all scheme is combined with traditional feature selection methods, such as ReliefF and LeastC. Also, one-versus-one scheme is utilized for alleviating the negative impact of a class imbalance problem arising from the one-versus-all scheme. Then, the relative contributions of features to thematic classes are obtained by the class-specific feature selection methods to describe the effectiveness of features for thematic information extraction. Finally, the class-specific feature selection methods are compared with the original methods on three different VHR image data sets by the nearest neighbor and support vector machine. Experimental results show that the class-specific feature selection methods outperform the corresponding conventional methods, and the one-versus-one scheme surpasses one-versus-all scheme. Additionally, many features are evaluated by the class-specific feature selection methods, to provide end users advice on effectiveness of the features.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	4837
Ending Page	4851
Page Count	15
File Size	4176433
File Format	PDF
ISSN	01962892
Volume Number	53
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Information retrieval Vectors Accuracy Robustness Data mining Image resolution thematic class Classification class-specific feature selection object-based features one-versus-one scheme
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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