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BEMD image fusion based on PCNN and compressed sensing

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Abstract

Bidimensional empirical mode decomposition (BEMD) is a new method for multi-scale image decomposition. In order to forbid useless information to cause an adverse impact on results and make the process have a better self-adaptability, this paper presents a new multi-scale image fusion method, which combines pulse coupled neural network (PCNN) and compressed sensing, and uses them in the BEMD. At first, BEMD processes the original images decomposed into multiple bidimensional intrinsic mode function (BIMFs) and a residual image. Then after doing compression measurement on each layer of BIMFS, we can get compression measurement coefficients. The coefficients at the same layer do the PCNN image fusion, and we can get measurement sampling BIMFs. And then after measurement sampling BIMFs reconstructed, we can get the final BIMFs. The residual images do the fusion based on entropy weight to get the final residual image. At last, after BEMD inverse transform, the final BIMFs and the final residual image get the result image. Experimental studies have shown that compared with other multi-scale decompositions-based image fusion algorithms, the algorithm in this paper has a better performance in terms of objective criteria and visual appearance.

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Acknowledgements

This work is supported by the National Natural Science Foundations of China (Nos. 61672522, 61379101) and the National Key Basic Research Program of China (No. 2013CB329502).

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Authors and Affiliations

  1. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China

    Shifei Ding, Peng Du, Xingyu Zhao & Qiangbo Zhu

  2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100090, China

    Shifei Ding

  3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Yu Xue

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  1. Shifei Ding
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  2. Peng Du
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  3. Xingyu Zhao
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  4. Qiangbo Zhu
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Correspondence to Shifei Ding.

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Shifei Ding declares that he has no conflict of interest. Peng Du declares that he has no conflict of interest. Xingyu Zhao declares that he has no conflict of interest. Qiangbo Zhu declares that he has no conflict of interest. Yu Xue declares that he has no conflict of interest.

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All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Additional informed consent was obtained from all patients for which identifying information is included in this article.

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This article does not contain any studies with human or animal subjects performed by the any of the authors.

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Communicated by V. Loia.

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Ding, S., Du, P., Zhao, X. et al. BEMD image fusion based on PCNN and compressed sensing. Soft Comput 23, 10045–10054 (2019). https://doi.org/10.1007/s00500-018-3560-8

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