Neural Processing Letters

, Volume 45, Issue 1, pp 75–94 | Cite as

Multi-focus Image Fusion Based on the Improved PCNN and Guided Filter

  • Zhaobin WangEmail author
  • Shuai Wang
  • Ying Zhu


This paper proposes a novel multi-focus image fusion method based on pulse coupled neural networks (PCNN) and guided filter. PCNN matches human visual perception very well. And guided filter is an edge-preserving filter which is proposed in recent years. In our method, the fusion process consists of the following steps: firstly, the source images are preliminarily fused with the guided filter. Then the intermediate fused image is employed to motivate the improved PCNN to generate a fusion map. Finally, the source images are fused according to the fusion map. Six contrast methods are employed to evaluate the performance of the proposed approach in six groups of experiments. The experimental results show that the proposed method outperforms the most existing methods in both subjective visual effect and objective evaluation criteria.


Image fusion Multi-focus image PCNN Guided filter Selection rule 



We thank the associate editor and the reviewers for their helpful and constructive suggestions. The authors also would like to express the profound thanks to Zheng Liu for his generous help. This work was jointly supported by China Postdoctoral Science Foundation (Grant No. 2013M532097), Fundamental Research Funds for the Central Universities (lzujbky-2014-52), National Science Foundation of China (Grant Nos. 61201421 & 61175012), and Science Foundation of Gansu Province of China (Grant No. 1208RJYA058).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Information Science and EngineeringLanzhou UniversityLanzhouChina
  2. 2.Institute of BiologyGansu Academy of SciencesLanzhouChina

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