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High-order nonnegative blind source separation based on edge features

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Abstract

The nonnegative blind source separation (NBSS) algorithm based on minimum volume simplex (MVS) criterion is excessively dependent on the shape of the mixture scatterplot, resulting in the situation in which the MVS-based algorithm may have no solution. In this paper, we propose a new noiseless NBSS model and introduce edge features into high-order determined NBSS. The edge feature-based NBSS model can compensate for the shortcomings of the MVS-based algorithm. The twice projections (TP) algorithm is designed to replace the existing clustering and regression algorithms; moreover, TP prevents the aliasing phenomenon caused by direct projection and effectively reduces the time complexity of dimension reduction. We search for the coordinates of the density maximum points in 2-D space, and gradually merge them into high-dimensional coordinates, which greatly reduces the complexity of the algorithm. Furthermore, we only make boundedness and nonnegativity assumptions about the source, which makes the algorithm more widely applicable.

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Acknowledgements

This work is supported by the Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB.

Funding

This work is supported by the Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB.

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Authors and Affiliations

  1. Information Engineering College of Hebei University of Architecture, Hebei University of Architecture, Zhangjiakou, 075000, China

    Mingzhan Zhao, Yingli Lv, Chunmei Du & Xiaojun Xu

  2. The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, 050081, China

    Weipeng Zheng

  3. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Zhiliang Wang

Authors
  1. Mingzhan Zhao
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  2. Weipeng Zheng
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  3. Yingli Lv
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  4. Chunmei Du
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  5. Zhiliang Wang
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  6. Xiaojun Xu
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Contributions

MingZhan wrote the main manuscript text, Xiaojun was in charge of the paper review, Weipeng was in charge of the paper layout, and other authors discussed and participated in the experiments.

Corresponding author

Correspondence to Xiaojun Xu.

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Zhao, M., Zheng, W., Lv, Y. et al. High-order nonnegative blind source separation based on edge features. SIViP 17, 4163–4170 (2023). https://doi.org/10.1007/s11760-023-02648-2

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  • DOI: https://doi.org/10.1007/s11760-023-02648-2

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