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Image processing using Newton-based algorithm of nonnegative matrix factorization

Author

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  • Hu, Li-Ying
  • Guo, Gong-De
  • Ma, Chang-Feng

Abstract

In this paper, we propose a Newton-based algorithm for nonnegative matrix factorization in image processing. We employ the new algorithm to three real-world databases. Extensive numerical results show the feasibility and validity of the proposed algorithm.

Suggested Citation

  • Hu, Li-Ying & Guo, Gong-De & Ma, Chang-Feng, 2015. "Image processing using Newton-based algorithm of nonnegative matrix factorization," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 956-964.
    • Handle: RePEc:eee:apmaco:v:269:y:2015:i:c:p:956-964
    DOI: 10.1016/j.amc.2015.08.034
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    References listed on IDEAS

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    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    2. Berry, Michael W. & Browne, Murray & Langville, Amy N. & Pauca, V. Paul & Plemmons, Robert J., 2007. "Algorithms and applications for approximate nonnegative matrix factorization," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 155-173, September.
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