A region-based multi-sensor image fusion scheme using pulse-coupled neural network

  • Authors:

  • Min Li;Wei Cai;Zheng Tan

  • Affiliations:

  • Department of Information and Communication Engineering, School of Electrics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shannxi Province 710049, PR China and Xi'an Research Ins ...;Xi'an Research Inst. of Hi-Tech Hongqing Town, Xi'an, Shaanxi 710025, PR China;Department of Information and Communication Engineering, School of Electrics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shannxi Province 710049, PR China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2006

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Abstract

For most image fusion algorithms split relationship among pixels and treat them more or less independently, this paper proposes a region-based image fusion scheme using pulse-coupled neural network (PCNN), which combines aspects of feature and pixel-level fusion. The basic idea is to segment all different input images by PCNN and to use this segmentation to guide the fusion process. In order to determine PCNN parameters adaptively, this paper brings forward an adaptive segmentation algorithm based on a modified PCNN with the multi-thresholds determined by a novel water region area method. Experimental results demonstrate that the proposed fusion scheme has extensive application scope and it outperforms the multi-scale decomposition based fusion approaches, both in visual effect and objective evaluation criteria, particularly when there is movement in the objects or mis-registration of the source images.