Using spanning graphs for efficient image registration

Mert R. Sabuncu, Peter Ramadge

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


We provide a detailed analysis of the use of minimal spanning graphs as an alignment method for registering multimodal images. This yields an efficient graph theoretic algorithm that, for the first time, jointly estimates both an alignment measure and a viable descent direction with respect to a parameterized class of spatial transformations. We also show how prior information about the interimage modality relationship from prealigned image pairs can be incorporated into the graph-based algorithm. A comparison of the graph theoretic alignment measure is provided with more traditional measures based on plug-in entropy estimators. This highlights previously unrecognized similarities between these two registration methods. Our analysis gives additional insight into the tradeoffs the graph-based algorithm is making and how these will manifest themselves in the registration algorithm's performance.

Original languageEnglish (US)
Pages (from-to)788-797
Number of pages10
JournalIEEE Transactions on Image Processing
Issue number5
StatePublished - May 2008

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design


  • Entropy
  • Estimation
  • Image registration


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