Paper
30 October 2009 A new method of multiscale image matching and application based on Fourier phase correlation
Dan pei Zhao, Hao Feng, Zhi guo Jiang
Author Affiliations +
Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74954W (2009) https://doi.org/10.1117/12.832827
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
In order to realize high-precision registration of high-resolution remote sensing image, an improved multi-scale phase correlation matching method is proposed based on wavelet modulus value. This method takes the advantages of wavelet multi-scale antinoise characteristics by replacing gray-scale information in traditional phase correlation method with the wavelet module value, thus it not only improved the matching accuracy, but also had a strong robustness for the image with illumination changes, blurring and occlusion. Furthermore, a coarse to fine match is adopted to reduce the computational complexity according to the capabilities of wavelet multi-resolution analysis, by which the algorithm is initialized by matching two low-resolution images and increasing the accuracy by applying the coarse matching result to high-resolution images. It is possible to meet the real-time requirement. From the experimental results, automatic registration is quickly realized for high-resolution remote sensing image under the complex background condition with strong noise jamming. Comparing with traditional phase correlation method, the improvement on both the higher robustness on noise and the processing speed is obvious.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan pei Zhao, Hao Feng, and Zhi guo Jiang "A new method of multiscale image matching and application based on Fourier phase correlation", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74954W (30 October 2009); https://doi.org/10.1117/12.832827
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KEYWORDS
Wavelets

Image resolution

Remote sensing

Wavelet transforms

Image registration

Fourier transforms

Image processing

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