论文信息 - Image Fusion Algorithm Based on PCNN and Wavelet Transform

Image Fusion Algorithm Based on PCNN and Wavelet Transform

For the better to simulate the process pattern of human eyes vision to fuse the images, taking the advantages of the merits of both PCNN and wavelet transform, a multi-resolution image fusion algorithm based on adaptive linking strength PCNN is proposed. This algorithm based on wavelet transform adopts PCNN of which the linking strength is local contrast, makes the different characteristics contented in the source images fuse into one image. the experiment results show that by using this algorithm, the mutual information between the images can be fused organically, the image clarity is raised, visual effect is improved greatly. Strong support for the information analysis and extractive ability of the images are provided.

Peng Li | Wen Ge | Wen Ge | Peng Li

[1] Eugene M. Izhikevich,et al. Class 1 neural excitability, conventional synapses, weakly connected networks, and mathematical foundations of pulse-coupled models , 1999, IEEE Trans. Neural Networks.

[2] Chen Shanben. Wavelet analysis and application in welding , 2003 .

[3] Heggere S. Ranganath,et al. Iterative segmentation using pulse-coupled neural networks , 1996, Defense + Commercial Sensing.

[4] Dai Ruo-lan,et al. Automated image segmentation using pulse coupled neural networks and images entropy , 2002 .

[5] M. Arndt,et al. A neural network for feature linking via synchronous activity: Results from cat visual cortex and from simulations , 1989 .

[6] Reinhard Eckhorn,et al. Neural mechanisms of scene segmentation: recordings from the visual cortex suggest basic circuits for linking field models , 1999, IEEE Trans. Neural Networks.

[7] Eugene M. Izhikevich,et al. Weakly pulse-coupled oscillators, FM interactions, synchronization, and oscillatory associative memory , 1999, IEEE Trans. Neural Networks.