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Novel multi-focus image fusion based on PCNN and random walks

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Abstract

The purpose of multi-focus image fusion is to acquire an image where all the objects are focused by fusing the source images which have different focus points. A novel multi-focus image fusion method is proposed in this paper, which is based on PCNN and random walks. PCNN is consistent with people’s visual perception. And the random walks model has been proven to have enormous potential to fuse image in recent years. The proposed method first employs PCNN to measure the sharpness of source images. Then, an original fusion map is constructed. Next, the method of random walks is employed to improve the accuracy of the fused regions detection. Finally, the fused image is generated according to the probability computed by random walks. The experiments demonstrate that our method outperforms many existing methods of multi-focus image fusion in visual perception and objective criteria. To assess the performance of our method in practical application, some examples are given at the end of paper.

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Acknowledgments

This work is jointly supported by China Postdoctoral Science Foundation (Grant No. 2013M532097), National Science Foundation of China (Grant No. 61201421), Special Foundation for Glacier Frozen Earth Talents Training Fund of China (Grant No.J1210003/J0109), The 12th Five-Year Informatization Project of the Chinese Academy of Sciences (Grant No.XXH12503-05-07).

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Authors and Affiliations

  1. Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou, 730000, China

    Zhaobin Wang

  2. School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, China

    Zhaobin Wang, Shuai Wang & Lijie Guo

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  1. Zhaobin Wang
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  2. Shuai Wang
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  3. Lijie Guo
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Correspondence to Zhaobin Wang.

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Wang, Z., Wang, S. & Guo, L. Novel multi-focus image fusion based on PCNN and random walks. Neural Comput & Applic 29, 1101–1114 (2018). https://doi.org/10.1007/s00521-016-2633-9

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