High-Dimensional Normalized Mutual Information for Image Registration Using Random Lines

  • A. Bardera
  • M. Feixas
  • I. Boada
  • M. Sbert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4057)


Mutual information has been successfully used as an effective similarity measure for multimodal image registration. However, a drawback of the standard mutual information-based computation is that the joint histogram is only calculated from the correspondence between individual voxels in the two images. In this paper, the normalized mutual information measure is extended to consider the correspondence between voxel blocks in multimodal rigid registration. The ambiguity and high-dimensionality that appears when dealing with the voxel neighborhood is solved using uniformly distributed random lines and reducing the number of bins of the images. Experimental results show a significant improvement with respect to the standard normalized mutual information.


Mutual Information Image Registration Normalize Mutual Information Entropy Rate Random Line 
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

  • A. Bardera
    • 1
  • M. Feixas
    • 1
  • I. Boada
    • 1
  • M. Sbert
    • 1
  1. 1.Institut d’Informàtica i AplicacionsUniversitat de GironaSpain

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