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Proceedings Paper

Selection of matching area in SAR scene-matching-aided navigation based on manifold learning
Author(s): Bin Li; Junbin Gong; Jinwen Tian
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Paper Abstract

Selection of suitable matching area is one of the key issues for image-matching-aided navigation system,but it is also a very challenging mission, especially with the multi-source image matching tasks. In this paper, a novel method to analyze the matching suitability of the satellite optical photograph to the realtime SAR in candidate flying regions is put forward. At first, several typical low-level image features are extracted. Then manifold learning is used to reduce the dimension of the sampled features, so as to generate new high-level image features with better discrimination ability. Finally, with the new features generated by manifold learning, we used support vector machines (SVM) to divide the candidate regions into two classes for suitable or unsuitable for matching. The experimental result shown that the proposed method is valid and effective.

Paper Details

Date Published: 8 December 2011
PDF: 8 pages
Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80021A (8 December 2011); doi: 10.1117/12.901886
Show Author Affiliations
Bin Li, Huazhong Univ. of Science and Technology (China)
Junbin Gong, Huazhong Univ. of Science and Technology (China)
China Ship Design and Research Ctr. (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8002:
MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis
Faxiong Zhang; Faxiong Zhang, Editor(s)

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