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Phase Correlation Based Image Alignment with Subpixel Accuracy

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Advances in Artificial Intelligence (MICAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7629))

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Abstract

The phase correlation method is a well-known image alignment technique with broad applications in medical image processing, image stitching, and computer vision. This method relies on estimating the maximum of the phase-only correlation (POC) function, which is defined as the inverse Fourier transform of the normalized cross-spectrum between two images. The coordinates of the maximum correspond to the translation between the two images. One of the main drawbacks of this method, in its basic form, is that the location of the maximum can only be obtained with integer accuracy. In this paper, we propose a new technique to estimate the location with subpixel accuracy, by minimizing the magnitude of gradient of the POC function around a point near the maximum. We also present some experimental results where the proposed method shows an increased accuracy of at least one order of magnitude with respect to the base method. Finally, we illustrate the application of the proposed algorithm to the rigid registration of digital images.

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Alba, A., Aguilar-Ponce, R.M., Vigueras-Gómez, J.F., Arce-Santana, E. (2013). Phase Correlation Based Image Alignment with Subpixel Accuracy. In: Batyrshin, I., González Mendoza, M. (eds) Advances in Artificial Intelligence. MICAI 2012. Lecture Notes in Computer Science(), vol 7629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37807-2_15

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  • DOI: https://doi.org/10.1007/978-3-642-37807-2_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37806-5

  • Online ISBN: 978-3-642-37807-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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