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Intensity based nonparametric image registration

Published: 29 March 2010 Publication History

Abstract

Image registration is used widely in applications for mapping one image to another. Existing image registration methods are either feature-based or intensity-based. Feature-based methods first extract relevant image features, and then find a geometrical transformation that best matches the two corresponding sets of features extracted from the two images. Because identification and extraction of image features is often a challenging and time-consuming process, intensity-based image registration, by which the mapping transformation is estimated directly from the observed image intensities of the two images, has received much attention recently. In the literature, most existing intensity-based image registration methods require a parametric form of the mapping transformation, which is restrictive for certain applications. In this paper, we propose an intensity-based image registration method without requiring such a parametric form. By this method, the mapping transformation can be nonparametric, and it can even be discontinuous at certain places in the design space. Numerical examples show that it is effective in various applications.

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Cited By

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  • (2018)Three-dimensional image registration using distributed parallel computingIET Image Processing10.1049/iet-ipr.2017.102112:10(1713-1720)Online publication date: 1-Oct-2018
  • (2013)Feature based image registration using non-degenerate pixelsSignal Processing10.1016/j.sigpro.2012.09.01393:4(706-720)Online publication date: Apr-2013
  • (2012)Multiscaled combination of MR and SPECT images in neuroimagingComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2010.07.012105:1(31-39)Online publication date: 1-Jan-2012

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cover image ACM Conferences
MIR '10: Proceedings of the international conference on Multimedia information retrieval
March 2010
600 pages
ISBN:9781605588155
DOI:10.1145/1743384
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 29 March 2010

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Author Tags

  1. degeneration
  2. edge detection
  3. local smoothing
  4. nonparametric transformation

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MIR '10
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MIR '10: International Conference on Multimedia Information Retrieval
March 29 - 31, 2010
Pennsylvania, Philadelphia, USA

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Cited By

View all
  • (2018)Three-dimensional image registration using distributed parallel computingIET Image Processing10.1049/iet-ipr.2017.102112:10(1713-1720)Online publication date: 1-Oct-2018
  • (2013)Feature based image registration using non-degenerate pixelsSignal Processing10.1016/j.sigpro.2012.09.01393:4(706-720)Online publication date: Apr-2013
  • (2012)Multiscaled combination of MR and SPECT images in neuroimagingComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2010.07.012105:1(31-39)Online publication date: 1-Jan-2012

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