Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models

Abstract — The operational segmentation of SAR sea ice imagery is a practical, challenging objective in the realm of applied pattern recognition. This research is in support of operational activities at the Canadian Ice Services (CIS), a government agency that monitors all ice-infested regions under...

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Bibliographic Details
Main Authors: David A. Clausi, Huawu Deng
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2005
Subjects:
Sea ice
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.1908
http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.126.1908 2023-05-15T18:16:42+02:00 Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models David A. Clausi Huawu Deng The Pennsylvania State University CiteSeerX Archives 2005 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.1908 http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.1908 http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf text 2005 ftciteseerx 2016-01-07T14:19:10Z Abstract — The operational segmentation of SAR sea ice imagery is a practical, challenging objective in the realm of applied pattern recognition. This research is in support of operational activities at the Canadian Ice Services (CIS), a government agency that monitors all ice-infested regions under Canadian jurisdiction. This paper uses a fusion of tone and texture to segment SAR sea ice images in an unsupervised manner. A novel Markov random field (MRF) segmentation technique is employed and produces improved results over K-means and the traditional MRF implementation. I. Text Sea ice Unknown
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description Abstract — The operational segmentation of SAR sea ice imagery is a practical, challenging objective in the realm of applied pattern recognition. This research is in support of operational activities at the Canadian Ice Services (CIS), a government agency that monitors all ice-infested regions under Canadian jurisdiction. This paper uses a fusion of tone and texture to segment SAR sea ice images in an unsupervised manner. A novel Markov random field (MRF) segmentation technique is employed and produces improved results over K-means and the traditional MRF implementation. I.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author David A. Clausi
Huawu Deng
spellingShingle David A. Clausi
Huawu Deng
Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
author_facet David A. Clausi
Huawu Deng
author_sort David A. Clausi
title Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
title_short Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
title_full Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
title_fullStr Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
title_full_unstemmed Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field models
title_sort unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel markov random field models
publishDate 2005
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.1908
http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf
genre Sea ice
genre_facet Sea ice
op_source http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.1908
http://www.eng.uwaterloo.ca/~dclausi/Papers/Clausi and Deng - PRRS 2004 - MRF Segmentation of SAR Sea Ice Images.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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