NDLI: Post-segmentation feature-based classification of synthetic aperture radar data

Content Provider	IEEE Xplore Digital Library
Author	Arini, N.S.
Copyright Year	2002
Description	Author affiliation: QinetiQ Ltd., Malvern, UK (Arini, N.S.)
Abstract	Classification is one of the most important image analysis tasks as it provides image data with labels that transform it into information about the real world. In this research, classification of clutter in single and multichannel very high-resolution airborne SAR imagery is achieved by extending several classification methodologies to overcome limitations which exist when applied to SAR data. This is achieved by first pre-processing the data using segmentation techniques, then classifying the resulting regions using a number of features calculated over the regions. By attempting to classify regions as opposed to single pixels we can increase the dimensionality of the feature space even for single channel data, and overcome the problems of speckle and texture inherent in SAR imagery. Both supervised and unsupervised classification methodologies have been adapted to feature-based region classification. The methodology has been extended to multichannel data, specifically polarimetric data. Examples of the application of the proposed method are given for several very high-resolution data sets from the QinetiQ airborne SAR. It is concluded that the proposed approach provides a successful and flexible, sensor independent solution to the problem of classification of very high-resolution SAR data for many different applications.
Sponsorship	IEEE IEEE Geosci. & Remote Sensing Soc. Canadian Remote Sensing Soc. Univ. Waterloo Natural Resources Canada (NRCan) Canadian Space Agency (CSA) Environ. Canada NASA Nat. Oceanic & Atmos. Adm. (NOAA) Office of Naval Res.(ONR) Nat. Space Dev. Agency of Japan (NASDA) Nat. Polar-orbiting Environ. Satellite Syst. (NPOESS)
Starting Page	1615
Ending Page	1617
File Size	677057
Page Count	3
File Format	PDF
ISBN	078037536X
DOI	10.1109/IGARSS.2002.1026198
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-06-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Synthetic aperture radar Layout Image segmentation Statistical distributions Pixel Speckle Image texture analysis Clutter Digital images Inference algorithms
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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