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Fast Wavelet Transform Based on Spiking Neural Network for Visual Images

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Emerging Intelligent Computing Technology and Applications (ICIC 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 375))

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Abstract

The functionalities of spiking neurons can be applied to deal with biological stimuli and explain complicated intelligent behaviorsof the brain. Wavelet transform is a powerful time-frequency analysis tool that can efficiently compress image and extract image features. In this article, a spiking neural network combined with the ON/OFF neuron arrays associated with the human visual system is proposed to perform the fast wavelet transform for visual images. The simulation results show that the spiking neural network can preserve the key features of visual images very well.

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Author information

Authors and Affiliations

  1. College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China

    Zhenmin Zhang, Qingxiang Wu, Zhiqiang Zhuo, Xiaowei Wang & Liuping Huang

Authors
  1. Zhenmin Zhang
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  2. Qingxiang Wu
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  3. Zhiqiang Zhuo
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  4. Xiaowei Wang
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  5. Liuping Huang
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Phalguni Gupta

  3. Tsinghua University, Beijing, China

    Ling Wang

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    Michael Gromiha

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© 2013 Springer-Verlag Berlin Heidelberg

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Zhang, Z., Wu, Q., Zhuo, Z., Wang, X., Huang, L. (2013). Fast Wavelet Transform Based on Spiking Neural Network for Visual Images. In: Huang, DS., Gupta, P., Wang, L., Gromiha, M. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2013. Communications in Computer and Information Science, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39678-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-39678-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39677-9

  • Online ISBN: 978-3-642-39678-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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