Multiscale kernel method for image matching

Hui Cheng; Jing Zhou; Shian Ma; Dajiang Shen; Jinwen Tian

doi:10.1117/12.749176

15 November 2007 Multiscale kernel method for image matching

Hui Cheng, Jing Zhou, Shian Ma, Dajiang Shen, Jinwen Tian

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861Y (2007) https://doi.org/10.1117/12.749176
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Hui Cheng, Jing Zhou, Shian Ma, Dajiang Shen, and Jinwen Tian "Multiscale kernel method for image matching", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861Y (15 November 2007); https://doi.org/10.1117/12.749176

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KEYWORDS

Wavelets

Image enhancement

Synthetic aperture radar

Feature extraction

Evolutionary algorithms

Distance measurement

Detection and tracking algorithms

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