New image fusion algorithm based on PCNN

Rui Xing Yu, Bing Zhu, Ke Zhang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

A novel algorithm based on Pulse Coupled Neural Network (PCNN) for image fusion was proposed. First, the two original images were decomposed by stationary wavelet transform, meanwhile, the two group multiscale sequences of each input images could be obtained. Secondly, one of the multiscale sequences were chosen arbitrarily as the input to the main PCNN network, and the others as the input to the subsidiary network. Then, sequences of multiscale fusion images were gotten by the parallel PCNN and the fused image could be obtained by inverse stationary wavelet transform at each process of iteration. At last, the optimal fusion result is obtained when the maximum value of the information entropy is achieved. Lots of experiments and comparisons with other fusion algorithms show the effectiveness and superiority of new method.

Original languageEnglish
Pages (from-to)126-130
Number of pages5
JournalGuangdian Gongcheng/Opto-Electronic Engineering
Volume35
Issue number1
StatePublished - Jan 2008

Keywords

  • Image fusion
  • Pulse coupled neural network (PCNN)
  • Stationary wavelet transform

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