Distributed high dimensional information theoretical image registration via random projections

Zoltán Szabó, András Lörincz

Research output: Contribution to journalArticle

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)894-902
Number of pages9
JournalDigital Signal Processing: A Review Journal
Issue number6
Publication statusPublished - Dec 2012


  • Distributed solution
  • High dimensional features
  • Information theoretical image registration
  • Random projection

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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