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Proceedings Paper

Multiscale kernel method for image matching
Author(s): Hui Cheng; Jing Zhou; Shian Ma; Dajiang Shen; Jinwen Tian
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Paper Abstract

In this paper, a new multiscale kernel function model is proposed, according to kernel function nature and the wavelet frame theory. Thus a new image support feature is defined based on the multiscale wavelet kernel regression for the purpose of improving image matching algorithm. The comprehensive the feature match and grey correlation method, a novel image fast matching algorithm is proposed based on support feature points. The partial Hausdorff distance is adopted as a similarity measure combined with the wavelet decomposition iteration to search the fine strategy, in the wavelet domain. According to support feature points the position in original image, extracts corresponding the grey value, and achieves the correlation matching. The matched data are compressed effectively because support feature points are sparse. Experimental results demonstrate that the proposed algorithm is robust, fast and can achieve matching accurately.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861Y (15 November 2007); doi: 10.1117/12.749176
Show Author Affiliations
Hui Cheng, Jianghan Univ. (China)
Huazhong Univ. of Science and Technology (China)
Jing Zhou, Huazhong Univ. of Science and Technology (China)
Jianghan Univ. (China)
Shian Ma, Jianghan Univ. (China)
Dajiang Shen, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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