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Geometric image registration under arbitrarily-shaped locally variant illuminations

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Abstract

In geometric image registration, illumination variations that exist between image pairs tend to degrade the precision of the registration, which can negatively affect subsequent processing. In this paper, we present a model to improve the sub-pixel geometric registration precision of image pairs when there exists locally variant illuminations with arbitrary shape. This model extends on our previous work to include multiple local shading levels of arbitrary shape, where the ill-posed problem is conditioned by constraining the solution to an estimated number of shading levels. The proposed model is solved using least-squares estimation and is cast in an iterative coarse-to-fine framework, which allows a convergence rate that is similar to competing intensity-based image registration approaches. The primary advantage of the proposed approach is the nearly tenfold improvement in sub-pixel precision for the registration when convergence is obtained in this class of technique.

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Authors and Affiliations

  1. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada

    M. M. Fouad, R. M. Dansereau & A. D. Whitehead

Authors
  1. M. M. Fouad
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  2. R. M. Dansereau
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  3. A. D. Whitehead
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Correspondence to R. M. Dansereau.

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Fouad, M.M., Dansereau, R.M. & Whitehead, A.D. Geometric image registration under arbitrarily-shaped locally variant illuminations. SIViP 6, 521–532 (2012). https://doi.org/10.1007/s11760-010-0178-4

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  • DOI: https://doi.org/10.1007/s11760-010-0178-4

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