A novel approach for image fusion based on Markov Random Fields

Min Xu, Hao Chen, Pramod Kumar Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Markov Random Field (MRF) model is a powerful tool to model image characteristics accurately and has been successfully applied to a large number of image processing applications. This paper investigates the problem of image fusion based on MRF models. A fusion algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithm.

Original languageEnglish (US)
Title of host publicationCISS 2008, The 42nd Annual Conference on Information Sciences and Systems
Pages344-349
Number of pages6
DOIs
StatePublished - 2008
EventCISS 2008, 42nd Annual Conference on Information Sciences and Systems - Princeton, NJ, United States
Duration: Mar 19 2008Mar 21 2008

Other

OtherCISS 2008, 42nd Annual Conference on Information Sciences and Systems
CountryUnited States
CityPrinceton, NJ
Period3/19/083/21/08

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ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering

Cite this

Xu, M., Chen, H., & Varshney, P. K. (2008). A novel approach for image fusion based on Markov Random Fields. In CISS 2008, The 42nd Annual Conference on Information Sciences and Systems (pp. 344-349). [4558549] https://doi.org/10.1109/CISS.2008.4558549