Multi-focus image fusion using PCNN

Authors:
Zhaobin Wang;Yide Ma;Jason Gu
Affiliations:
School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China and Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Nova Scotia, Canada B ...;School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China;Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Nova Scotia, Canada B3J 2X4
Venue:
Pattern Recognition
Year:
2010

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Abstract

This paper proposes a new method for multi-focus image fusion based on dual-channel pulse coupled neural networks (dual-channel PCNN). Compared with previous methods, our method does not decompose the input source images and need not employ more PCNNs or other algorithms such as DWT. This method employs the dual-channel PCNN to implement multi-focus image fusion. Two parallel source images are directly input into PCNN. Meanwhile focus measure is carried out for source images. According to results of focus measure, weighted coefficients are automatically adjusted. The rule of auto-adjusting depends on the specific transformation. Input images are combined in the dual-channel PCNN. Four group experiments are designed to testify the performance of the proposed method. Several existing methods are compared with our method. Experimental results show our presented method outperforms existing methods, in both visual effect and objective evaluation criteria. Finally, some practical applications are given further.