Kernel-Predictability: A New Information Measure and Its Application to Image Registration

  • Héctor Fernando Gómez-García
  • José L. Marroquín
  • Johan Van Horebeek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3953)


A new information measure for probability distributions is presented; based on it, a similarity measure between images is derived, which is used for constructing a robust image registration algorithm based on random sampling, similar to classical approaches like mutual information. It is shown that the registration method obtained with the new similarity measure shows a significantly better performance for small sampling sets; this makes it specially suited for the estimation of non-parametric deformation fields, where the estimation of the local transformation is done on small windows. This is confirmed by extensive comparisons using synthetic deformations of real images.


Mutual Information Image Registration Information Measure Registration Method Normalize Mutual Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Héctor Fernando Gómez-García
    • 1
  • José L. Marroquín
    • 1
  • Johan Van Horebeek
    • 1
  1. 1.Center for Research in Mathematics (CIMAT)GuanajuatoMéxico

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