Pulse coupled neural network based image fusion

  • Authors:

  • Min Li;Wei Cai;Zheng Tan

  • Affiliations:

  • School of Electronics and Information Engineering, Xi'an Jiaotong University and Xi'an Research Inst. of Hi-Tech Hongqing Town, Xi'an, Shaanxi, China;Xi'an Research Inst. of Hi-Tech Hongqing Town, Shaanxi, China;School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
  • Year:
  • 2005

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Abstract

For the pulse-coupled neural network (PCNN) has an inherent ability to segment images, we present a multisensor image fusion scheme based on PCNN in this paper. The algorithm adopts salience and visibility as two extracted features for each segmented region to determine the fusion weight. Extensive experimental results have demonstrated that the proposed method has extensive application scope and it outperforms the discrete wavelet transform approach, both in visual effect and objective evaluation criteria, particularly when there is movement in the objects or mis-registration of the source images