Comparative Analysis of Image Fusion Performance Evaluation Methods for the Real-Time Environment Monitoring System

  • Maciej Wielgus
  • Barbara Putz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 184)


We discuss and compare several objective measures used for image fusion algorithm performance evaluation. Subjective assessments are given as well. Many of the considered evaluation methods originate from prior literature, we also introduce measure based on Jensen-Shannon divergence and a simple gradient-based measure, particularly well fitted for the real time fusion evaluation issue. Along with several well known fusion methods we put under tests recently developed, promising algorithm based on the fast and adaptive bidimensional empirical mode decomposition.


Image Fusion Empirical Mode Decomposition Shannon Entropy Fusion Algorithm Fusion Result 
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 2013

Authors and Affiliations

  1. 1.Institute of Micromechanics and PhotonicsWarsawPoland
  2. 2.Institute of Automatic Control and RoboticsWarsawPoland

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