Multisource Image Fusion Based on DWT and Simplified Pulse Coupled Neural Network

Abstract:

In this paper, a new image fusion algorithm based on discrete wavelet transform (DWT) and spiking cortical model (SCM) is proposed. The multiscale decomposition and multi-resolution representation characteristics of DWT are associated with global coupling and pulse synchronization features of SCM. Two different fusion rules are used to fuse the low and high frequency sub-bands respectively. Maximum selection rule (MSR) is used to fuse low frequency coefficients. As to high frequency subband coefficients, spatial frequency (SF) is calculated and then imputed into SCM to motivate neural network. Experimental results demonstrate the effectiveness of the proposed fusion method.

• Periodical: Applied Mechanics and Materials (Volumes 457-458)
• Pages: 736-740
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.457-458.736
• Online since: October 2013
• Authors: Nian Yi Wang, Wei Lan Wang, Xiao Ran Guo
• Keywords: Discrete Wavelet Transform (DWT), Multisource Image Fusion, Simplified PCNN, Spatial Frequency, Spiking Cortical Model (SCM)

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