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Acta Automatica Sinica


DOI: 10.3724/SP.J.1004.2008.01508

Acta Automatica Sinica 2008/34 :12 PP.1508-1514

Papers and Reports

Image Fusion Algorithm Based on Spatia Frequency-Motivated Pulse Coupled Neural Networks in Nonsubsampled Contourlet Transform Domain

QU Xiao-Bo 1 , YAN Jing-Wen 1, 2 , XIAO Hong-Zhi 2 & ZHU Zi-Qian 3

1. Department of Communication Engineering, Xiamen University, Xiamen, 361005, P.R.China
2. Key Laboratory of Digital Signal and Image Processing of Guangdong Province, Shantou University, Shantou, 515063, P.R.China
3. Research Institute of Chinese Radar Electronic Equipment, Wuxi, 214063, P.R.China

Abstract: Nonsubsampled contourlet transform (NSCT) provides flexible multiresolution, anisotropy, and directional expansion for images.Compared with the original contourlet transform, it is shift-invariant and can overcome the pseudo-Gibbs phenomena around singularities. Pulse coupled neural networks (PCNN) is a visual cortex-inspired neural network and characterized by the global coupling and pulse synchronization of neurons. It has been proven suitable for image processing and successfully employed in image fusion.In this paper, NSCT is associated with PCNN and used in image fusion to make full use of the characteristics of them.Spatial frequency in NSCT domain is input to motivate PCNN and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Experimental results demonstrate that the proposed algorithm outperforms typical wavelet-based, contourlet-based, PCNN-based, and contourlet-PCNN based fusion algorithms in terms of objective criteria and visual appearance.

Keywords: Contourlet, pulse coupled neural networks (PCNN), wavelet,image fusion, multiscale transform 

Recieved: 2007-11-29 ; Accepted: 2008-03-29; Published Online: 2009-04-07

Corresponding Author: QU Xiao-Bo (qxb_xmu@yahoo.com.cn)

Supported By:Supported by National Natural Science Foundation of China(60472081) and Navigation Science Foundation of China (05F07001)