A New Method for Sub-Pixel TDICCD Image Registration

Bin He

doi:10.4028/www.scientific.net/AMM.325-326.1610

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 325-326A New Method for Sub-Pixel TDICCD Image...

A New Method for Sub-Pixel TDICCD Image Registration

Abstract:

This paper presents a more accurate and faster method for sub-pixel TDICCD image registration. The method makes the best of the overlapping pixels between multi-channel images, which allows for scaling, translation and rotation. Secondly, the proposed technique combines an efficient pixel-moving interpolation scheme with surface fitting, which makes use of accurate interpolation calculation and fast surface fitting in the iterative process. Finally, the accuracy and speed of the algorithm is evaluated by sub-pixel registration of multi-channel images and comparison with other sorts of efficient methods. The experiment results show that the accuracy of the method reaches 0.01 pixels and it is 3 times faster than the interpolation method.

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Periodical:

Applied Mechanics and Materials (Volumes 325-326)

Pages:

1610-1613

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.325-326.1610

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Online since:

June 2013

Authors:

Bin He

Keywords:

Iterative Pixel Interpolation, Large Field View, Multi-Channel, Surface Fitting, TDICCD

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References

[1] C. Kuglin, D. Hines, "The Phase Correlation Image Alignment Method," [C]// Proceedings IEEE International Conference on Cybernetics and Society, Vol. 3, l975, pp.163-165.

Google Scholar

[2] SZELISKI R, Video mosaics for virtual environments, [J], IEEE Computer Graphics and Applications, Vol. 16, 1996, pp.22-30.

DOI: 10.1109/38.486677

Google Scholar

[3] H.S. Stone, M.T. Orchard, E.C. Chang, and S.A. Matrucci, "A fast direct Fourier-based algorithm for subpixel registration of images," IEEE Trans. Geosci. Remote Sensing, Vol. 39, 2001, p.2235–2243.

DOI: 10.1109/36.957286

Google Scholar

[4] P. Thevenaz, U.E. Ruttimann, M. Unser "A pyramidal approach to subpixel registration based on intensity," IEEE Trans. Image Process, Vol. 7, 1998, p.27–41.

DOI: 10.1109/83.650848

Google Scholar

[5] U. Koc, K.J.R. Liu, "Interpolation-free subpixel motion estimation techniques in dct," IEEE Trans. on Circuit and System for Video Technology, Vol. 8, 1998, p.460~487.

DOI: 10.1109/76.709412

Google Scholar