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Limited Memory Methods with Improved Symmetric Rank-one Updates and Its Applications on Nonlinear Image Restoration

  • Research Article - Computer Engineering and Computer Science
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Abstract

The iterative solution of unconstrained optimization problems has been found in a variety of significant applications of research areas, such as image restoration. In this paper, we present an efficient limited memory quasi-Newton technique based on symmetric rank-one updating formula to compute meaningful solutions for large-scale problems arising in some image restoration problems. Numerical experiments and comparisons on various well-known methods in the literature are presented to illustrate the effectiveness of the proposed method particularly for images of large size.

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Authors and Affiliations

  1. Department of Mathematics, College of Sciences, Tabriz Branch, Islamic Azad University, Tabriz, Iran

    Farzin Modarres Khiyabani

  2. Department of Mathematics, Faculty of Science, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    Wah June Leong

Authors
  1. Farzin Modarres Khiyabani
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  2. Wah June Leong
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Correspondence to Farzin Modarres Khiyabani.

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Modarres Khiyabani, F., Leong, W.J. Limited Memory Methods with Improved Symmetric Rank-one Updates and Its Applications on Nonlinear Image Restoration. Arab J Sci Eng 39, 7823–7838 (2014). https://doi.org/10.1007/s13369-014-1357-3

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  • DOI: https://doi.org/10.1007/s13369-014-1357-3

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