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POLSAR IMAGE SEGMENTATION BASED ON HIERARCHICAL REGION MERGING AND SEGMENT REFINEMENT WITH WMRF MODEL
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
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2017 (English)In: 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), IEEE , 2017, p. 4574-4577Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a superpixel-based segmentation method is proposed for PolSAR images by utilizing hierarchical region merging and segment refinement. The loss of the energy function, which determines the consistency of two adjacent regions from the statistical aspect, is applied to guide the merging procedure. In addition to the edge penalty term, the homogeneity measurement is also employed to prevent merging the regions that are from different land covers or objects. Based on the merged segments, the segment refinement is applied to further improve the segmentation accuracy by iteratively relabeling the edge pixels. It uses a maximum a posterior (MAP) criterion using the statistical distribution of the pixels and the Markov random field (MRF) model. The performance of the proposed method is validated on an experimental PolSAR dataset from the ESAR system.

Place, publisher, year, edition, pages
IEEE , 2017. p. 4574-4577
Series
IEEE International Symposium on Geoscience and Remote Sensing IGARSS, ISSN 2153-6996
Keywords [en]
Polarimetric synthetic aperture radar (PolSAR), segmentation, hierarchical merging, Markov random field (MRF)
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-226279ISI: 000426954604156Scopus ID: 2-s2.0-85041809428ISBN: 978-1-5090-4951-6 OAI: oai:DiVA.org:kth-226279DiVA, id: diva2:1198960
Conference
IEEE International Geoscience & Remote Sensing Symposium, JUL 23-28, 2017, Fort Worth, TX
Note

QC 20180419

Available from: 2018-04-19 Created: 2018-04-19 Last updated: 2018-04-19Bibliographically approved

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Wang, WeiBan, Yifang

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  • apa
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Output format
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