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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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
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