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Entropy-based image registration method using the curvelet transform

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Abstract

Registration is a prerequisite for fusion of geometrically distorted images. Traditionally, intensity-based image registration methods are preferred to feature-based ones due to higher accuracy of the former than that of the latter. To reduce computational load, image registration is often carried out using the approximate-level coefficients of a wavelet-like transform. Directional selectivity of the transform and the objective function used for the coefficients play vital roles in the alignment process of images. This paper introduces an image registration algorithm that uses the approximate-level coefficients of the curvelet transform, directional selectivity of which is better than many wavelet-like transforms. A conditional entropy-based objective function is developed for registration using a suitable probabilistic model of the curvelet coefficients of images. Suitability of the probability distribution of the coefficients is validated using a standard method to assess goodness of fit. To align the distorted images, the affine transformation that possesses parameters related to the translation, rotation, scaling, and shearing is used. Extensive experimentations are carried out to test the performance of the proposed registration method considering that the images are synthetically or naturally distorted. Experimental results show that performance of the proposed registration method is superior to existing methods in terms of commonly used performance metrics.

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Author notes

  1. S. M. Mahbubur Rahman

    Present address: Edward S. Rogers Sr. Department of ECE, University of Toronto, 40 St. George Street, BAHEN Bld. Room 4154, Toronto, ON, M5S 2E4, Canada

Authors and Affiliations

  1. School of Electrical and Computer Engineering, Oklahoma State University, 202 Engineering South, Stillwater, OK, 74078-5032, USA

    Md. Mushfiqul Alam

  2. Institute of Statistical Research and Training, Dhaka University, Dhaka, 1000, Bangladesh

    Tamanna Howlader

  3. Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh

    S. M. Mahbubur Rahman

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  1. Md. Mushfiqul Alam
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Correspondence to S. M. Mahbubur Rahman.

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Alam, M.M., Howlader, T. & Rahman, S.M.M. Entropy-based image registration method using the curvelet transform. SIViP 8, 491–505 (2014). https://doi.org/10.1007/s11760-012-0394-1

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