Image Segmentation Using Binary Tree Structured Markov Random Fields

Synthetic Aperture Radar (SAR) systems are important active sensors for Earth observation systems. They enable continuous monitoring of the targets (e.g., sea ice, agricultural areas, ships, etc.) through clouds and independent of solar illumination. Space-borne polarimetric SAR missions which are p...

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Bibliographic Details
Main Author: Kaan Ersahin
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2004
Subjects:
Sea ice
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.141
http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.136.141 2023-05-15T18:17:38+02:00 Image Segmentation Using Binary Tree Structured Markov Random Fields Kaan Ersahin The Pennsylvania State University CiteSeerX Archives 2004 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.141 http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.141 http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf text 2004 ftciteseerx 2016-01-07T14:43:15Z Synthetic Aperture Radar (SAR) systems are important active sensors for Earth observation systems. They enable continuous monitoring of the targets (e.g., sea ice, agricultural areas, ships, etc.) through clouds and independent of solar illumination. Space-borne polarimetric SAR missions which are planned for the near future draw our attention to the crucial task of information extraction from such data. The Text Sea ice Unknown
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description Synthetic Aperture Radar (SAR) systems are important active sensors for Earth observation systems. They enable continuous monitoring of the targets (e.g., sea ice, agricultural areas, ships, etc.) through clouds and independent of solar illumination. Space-borne polarimetric SAR missions which are planned for the near future draw our attention to the crucial task of information extraction from such data. The
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Kaan Ersahin
spellingShingle Kaan Ersahin
Image Segmentation Using Binary Tree Structured Markov Random Fields
author_facet Kaan Ersahin
author_sort Kaan Ersahin
title Image Segmentation Using Binary Tree Structured Markov Random Fields
title_short Image Segmentation Using Binary Tree Structured Markov Random Fields
title_full Image Segmentation Using Binary Tree Structured Markov Random Fields
title_fullStr Image Segmentation Using Binary Tree Structured Markov Random Fields
title_full_unstemmed Image Segmentation Using Binary Tree Structured Markov Random Fields
title_sort image segmentation using binary tree structured markov random fields
publishDate 2004
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.141
http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf
genre Sea ice
genre_facet Sea ice
op_source http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.141
http://www.cs.ubc.ca/~murphyk/Teaching/CS532c_Fall04/Projects/erashin.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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