Distributed high dimensional information theoretical image registration via random projections
Zoltan Szabo and András Lorincz
Digital Signal Processing 2012.

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Abstract

Information theoretical measures, such as entropy, mutual information, and various divergences, exhibit robust characteristics in image registration applications. However, the estimation of these quantities is computationally intensive in high dimensions. On the other hand, consistent estimation from pairwise distances of the sample points is possible, which suits random projection (RP) based low dimensional embeddings. We adapt the RP technique to this task by means of a simple ensemble method. To the best of our knowledge, this is the first distributed, RP based information theoretical image registration approach. The efficiency of the method is demonstrated through numerical examples.

Available Versions of this Item

• Distributed high dimensional information theoretical image registration via random projections (deposited 11 July 2012) [Currently Displayed]
  • Distributed high dimensional information theoretical image registration via random projections (deposited 10 October 2012)

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