An Effective Technique for Subpixel Image Registration Under Noisy Conditions

Authors:
Li Chen;Kim-Hui Yap
Affiliations:
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Year:
2008

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Abstract

This paper proposes an effective higher order statistics method to address subpixel image registration. Conventional power spectrum-based techniques employ second-order statistics to estimate subpixel translation between two images. They are, however, susceptible to noise, thereby leading to significant performance deterioration in low signal-to-noise ratio environments or in the presence of cross-correlated channel noise. In view of this, we propose a bispectrum-based approach to alleviate this difficulty. The new method utilizes the characteristics of bispectrum to suppress Gaussian noise. It develops a phase relationship between the image pair and estimates the subpixel translation by solving a set of nonlinear equations. Experimental results show that the proposed technique provides performance improvement over conventional power-spectrum-based methods under different noise levels and conditions.