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Modified particle swarm optimization and fuzzy regularization for pseudo de-convolution of spatially variant blurs

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Abstract

We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-convolution of the ill-posed inverse problem namely, the space-variant image degradation (SVD). In this paper, SVD is simulated by the pseudo convolution of different sub-regions of the image with different known blurring kernels and additive random noise with unknown variance. Two heuristic modifications are proposed in PSO: 1) Initialization of the swarm and 2) Mutation of the global best. Fuzzy logic is applied for the computation of regularization parameter (RP) to cater for the sensitivity of the problem. The computation of RP is crucial due to the additive noise in the SVD image. Thus mathematical morphology (MM) is applied for better extraction of spatial activity from the distorted image. The performance of the proposed method is evaluated with different test images and noise powers. Comparative analysis demonstrates the superiority of proposed restoration, in terms of quantitative measures, over well-known existing and state-of-the-art SVD approaches.

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Acknowledgments

Authors would acknowledge Higher Education Commission (HEC) of Pakistan, for its continuous financial support in the meritorious role of scholarship for higher education.

Authors would like to thank the anonymous reviewers for their comments and suggestions that helped to substantially improve this paper.

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Authors and Affiliations

  1. Computer Science Department, National University of Computer And Emerging Sciences, A.K. Brohi Road, H-11/4, Islamabad, Pakistan

    Mohsin Bilal & Hasan Mujtaba

  2. College of Computer and Information Systems, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

    Muhammad Arfan Jaffar

Authors
  1. Mohsin Bilal
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  2. Hasan Mujtaba
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  3. Muhammad Arfan Jaffar
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Corresponding author

Correspondence to Mohsin Bilal.

Additional information

Furthermore, “Some/all of the data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non-HST data is provided by the NASA Office of Space Science via grant NNX13AC07G and by other grants and contracts.”

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Bilal, M., Mujtaba, H. & Jaffar, M.A. Modified particle swarm optimization and fuzzy regularization for pseudo de-convolution of spatially variant blurs. Multimed Tools Appl 75, 6533–6548 (2016). https://doi.org/10.1007/s11042-015-2587-4

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