A new image fusion algorithm based on adaptive PCNN

Mei Li Li, Yan Jun Li, Hong Mei Wang, Ke Zhang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Owing to the global coupling and pulse synchronization characteristic, pulse coupled neural networks(PCNN) has been proved to be suitable for image fusion. In this paper, a new image fusion algorithm based on adaptive PCNN is presented. Compared with the traditional algorithms where the linking strength of each neuron is assigned the same value, this algorithm uses the features of each pixel, e.g. energy of Laplacian and standard deviation, as its value, so that the linking strength of each pixel can be chosen adaptively. Experimental results demonstrate that the proposed algorithm outperforms Laplacian-based, wavelet-based and PCNN-based fusion algorithms.

Original languageEnglish
Pages (from-to)779-782
Number of pages4
JournalGuangdianzi Jiguang/Journal of Optoelectronics Laser
Volume21
Issue number5
StatePublished - May 2010

Keywords

  • Energy of Laplacian(EOL)
  • Features
  • Image fusion
  • Linking strength
  • Pulse coupled neural networks(PCNN)
  • Standard deviation(SD)

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