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Fast Bi-dimensional empirical mode decomposition(BEMD) based on variable neighborhood window method

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Abstract

This paper presents a new method for BEMD. BEMD can decompose a source image into several two-dimensional intrinsic mode functions. During the image decomposition process, it is required to interpolate and draw the upper and lower envelopes. However, these interpolations and drawing the enveloping surface require a large amount of computing time and artificial screening. Thus, some scholars proposed the rapid realization of BEMD. Further, the window size being fixed during the decomposition process led to losses in the data-driven characteristics, adaptability and dimension consistency of the original BEMD. Therefore, this paper proposes a simple but effective means of keeping the original BEMD method features. The estimate reconstruction method is used to replace surface interpolation, and the variable neighborhood window method is adopted to replace the fixed neighborhood window method. In this article, an order filter is used to reconstruct the upper and lower envelopes, and then the filter size is obtained by using the fact that the image information itself is adaptively variable. Through an empirical analysis, this paper shows that this method can keep the original BEMD method’s rapid decomposition, data-driven characteristics, adaptivity and consistency of scale.

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Acknowledgements

This work is supported by National Science Foundation Project of P. R. China (No. 61701188) and the Foundation of Science and Technology on Information Assurance Laboratory (No.KJ-17-101).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, 100083, People’s Republic of China

    Xingmin Ma & Xianwei Zhou

  2. Huai-yin Normal of University, Huai-an, China

    FengPing An

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  1. Xingmin Ma
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  2. Xianwei Zhou
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  3. FengPing An
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Correspondence to Xingmin Ma.

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Ma, X., Zhou, X. & An, F. Fast Bi-dimensional empirical mode decomposition(BEMD) based on variable neighborhood window method. Multimed Tools Appl 78, 8889–8910 (2019). https://doi.org/10.1007/s11042-018-6629-6

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