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POLSAR IMAGE SEGMEN...
POLSAR IMAGE SEGMENTATION BASED ON HIERARCHICAL REGION MERGING AND SEGMENT REFINEMENT WITH WMRF MODEL
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- Wang, Wei (författare)
- KTH,Geoinformatik
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- Zhai, Qinglin (författare)
- Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China.
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- Ban, Yifang (författare)
- KTH,Geoinformatik
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- Zhang, Jun (författare)
- Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China.
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- Wan, Jianwei (författare)
- Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China.
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(creator_code:org_t)
- IEEE, 2017
- 2017
- Engelska.
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Ingår i: 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). - : IEEE. - 9781509049516 ; , s. 4574-4577
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Nyckelord
- Polarimetric synthetic aperture radar (PolSAR)
- segmentation
- hierarchical merging
- Markov random field (MRF)
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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