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Neural Computing and Applications

Erschienen in:

22.10.2016 | Original Article

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

verfasst von: Zhaobin Wang, Shuai Wang, Lijie Guo

Erschienen in: Neural Computing and Applications | Ausgabe 11/2018

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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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Titel: Novel multi-focus image fusion based on PCNN and random walks
verfasst von: Zhaobin Wang
Shuai Wang
Lijie Guo
Publikationsdatum: 22.10.2016
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 11/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-016-2633-9

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