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Multi-Focus Image Fusion Using Pulse Coupled Neural Network

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Non-Cooperative Target Tracking, Fusion and Control

Part of the book series: Information Fusion and Data Science ((IFDS))

Abstract

Multi-focus image fusion is a significant preprocessing procedure to obtain a clear image by fusing single-focus images. This chapter introduces a multi-focus image fusion method based on image blocks and pulse coupled neural network (PCNN). First, registered source images are divided into blocks. Then energy of image Laplacian is used to generate feature maps. The feature maps are used as external stimulus to be inputs of PCNN. Finally, the fused image will be obtained by comparing the outputs of PCNN. Comprehensive experiments are conducted to show the performance of our proposed method. It outperforms some previous fusion methods in three datasets.

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Author information

Authors and Affiliations

  1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

    Zhongliang Jing & Han Pan

  2. University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    Yuankai Li

  3. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, Shanghai, China

    Peng Dong

Authors
  1. Zhongliang Jing
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  2. Han Pan
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  3. Yuankai Li
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  4. Peng Dong
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Jing, Z., Pan, H., Li, Y., Dong, P. (2018). Multi-Focus Image Fusion Using Pulse Coupled Neural Network. In: Non-Cooperative Target Tracking, Fusion and Control. Information Fusion and Data Science. Springer, Cham. https://doi.org/10.1007/978-3-319-90716-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-90716-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90715-4

  • Online ISBN: 978-3-319-90716-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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